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Background: A clearer understanding of the etiological overlap between DSM-IV personality disorders (PDs) and alcohol use (AU) and alcohol use disorder (AUD) is needed. To our knowledge, no study has modeled the association between all 10 DSM-IV PDs and lifetime AU and AUD. The aim of the present study is to identify which PDs are most strongly associated with the phenotypic, genetic, and environmental risks of lifetime AU and AUD, and to determine if these associations are stable across time., Methods: Participants were Norwegian twins assessed at two waves. At Wave 1, 2801 twins were assessed for all 10 DSM-IV PD criteria, lifetime AU, and DSM-IV AUD criteria. At Wave 2, six of the 10 PDs were again assessed along with AU and AUD among 2393 twins. Univariate and multiple logistic regressions were run. Significant predictors were further analyzed using bivariate twin Cholesky decompositions., Results: Borderline and antisocial PD criteria were the strongest predictors of AU and AUD across the two waves. Despite moderate phenotypic and genetic correlations, genetic variation in these PD criteria explained only 4% and 3% of the risks in AU, and 5% to 10% of the risks in AUD criteria, respectively. At Wave 2, these estimates increased to 8% and 23% for AU, and 17% and 33% for AUD., Conclusions: Among a large Norwegian twin sample, borderline and antisocial PD criteria were the strongest predictors of the phenotypic and genotypic liability to AU and AUD. This effect remained consistent across time., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Sequence-based association studies are at a critical inflexion point with the increasing availability of exome-sequencing data. A popular test of association is the sequence kernel association test (SKAT). Weights are embedded within SKAT to reflect the hypothesized contribution of the variants to the trait variance. Because the true weights are generally unknown, and so are subject to misspecification, we examined the efficiency of a data-driven weighting scheme. We propose the use of a set of theoretically defensible weighting schemes, of which, we assume, the one that gives the largest test statistic is likely to capture best the allele frequency-functional effect relationship. We show that the use of alternative weights obviates the need to impose arbitrary frequency thresholds. As both the score test and the likelihood ratio test (LRT) may be used in this context, and may differ in power, we characterize the behavior of both tests. The two tests have equal power, if the weights in the set included weights resembling the correct ones. However, if the weights are badly specified, the LRT shows superior power (due to its robustness to misspecification). With this data-driven weighting procedure the LRT detected significant signal in genes located in regions already confirmed as associated with schizophrenia - the PRRC2A (p = 1.020e-06) and the VARS2 (p = 2.383e-06) - in the Swedish schizophrenia case-control cohort of 11,040 individuals with exome-sequencing data. The score test is currently preferred for its computational efficiency and power. Indeed, assuming correct specification, in some circumstances, the score test is the most powerful test. However, LRT has the advantageous properties of being generally more robust and more powerful under weight misspecification. This is an important result given that, arguably, misspecified models are likely to be the rule rather than the exception in weighting-based approaches.

Introduction: Previous studies in adolescents were not adequately powered to accurately disentangle genetic and environmental influences on smoking initiation (SI) across adolescence., Methods: Mega-analysis of pooled genetically informative data on SI was performed, with structural equation modeling, to test equality of prevalence and correlations across cultural backgrounds, and to estimate the significance and effect size of genetic and environmental effects according to the classical twin study, in adolescent male and female twins from same-sex and opposite-sex twin pairs (N = 19 313 pairs) between ages 10 and 19, with 76 358 longitudinal assessments between 1983 and 2007, from 11 population-based twin samples from the United States, Europe, and Australia., Results: Although prevalences differed between samples, twin correlations did not, suggesting similar etiology of SI across developed countries. The estimate of additive genetic contributions to liability of SI increased from approximately 15% to 45% from ages 13 to 19. Correspondingly, shared environmental factors accounted for a substantial proportion of variance in liability to SI at age 13 (70%) and gradually less by age 19 (40%)., Conclusions: Both additive genetic and shared environmental factors significantly contribute to variance in SI throughout adolescence. The present study, the largest genetic epidemiological study on SI to date, found consistent results across 11 studies for the etiology of SI. Environmental factors, especially those shared by siblings in a family, primarily influence SI variance in early adolescence, while an increasing role of genetic factors is seen at later ages, which has important implications for prevention strategies., Implications: This is the first study to find evidence of genetic factors in liability to SI at ages as young as 12. It also shows the strongest evidence to date for decay of effects of the shared environment from early adolescence to young adulthood. We found remarkable consistency of twin correlations across studies reflecting similar etiology of liability to initiate smoking across different cultures and time periods. Thus familial factors strongly contribute to individual differences in who starts to smoke with a gradual increase in the impact of genetic factors and a corresponding decrease in that of the shared environment., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

There is evidence that differences among individuals in white matter microstructure, as measured with diffusion tensor imaging (DTI), are under genetic control. However, little is known about the relative contribution of genetic and environmental effects on different diffusivity indices among late middle-aged adults. Here, we examined the magnitude of genetic influences for fractional anisotropy (FA), and mean (MD), axial (AD), and radial (RD) diffusivities in male twins aged 56-66 years old. Using an atlas-based registration approach to delineate individual white matter tracts, we investigated mean DTI-based indices within the corpus callosum, 12 bilateral tracts and all these regions of interest combined. All four diffusivity indices had high heritability at the global level (72%-80%). The magnitude of genetic effects in individual tracts varied from 0% to 82% for FA, 0% to 81% for MD, 8% to 77% for AD, and 0% to 80% for RD with most of the tracts showing significant heritability estimates. Despite the narrow age range of this community-based sample, age was correlated with all four diffusivity indices at the global level. In sum, all diffusion indices proved to have substantial heritability for most of the tracts and the heritability estimates were similar in magnitude for different diffusivity measures. Future studies could aim to discover the particular set of genes that underlie the significant heritability of white matter microstructure. Hum Brain Mapp 38:2026-2036, 2017. © 2017 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

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-5-Norwegian Brief Form (PID-5-NBF). 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-5-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-5-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.

Magnetic resonance imaging (MRI) has become an important tool in the early detection of age-related and neuropathological brain changes. Recent studies suggest that changes in mean diffusivity (MD) of cortical gray matter derived from diffusion MRI scans may be useful in detecting early effects of Alzheimer's disease (AD), and that these changes may be detected earlier than alterations associated with standard structural MRI measures such as cortical thickness. Thus, due to its potential clinical relevance, we examined the genetic and environmental influences on cortical MD in middle-aged men to provide support for the biological relevance of this measure and to guide future gene association studies. It is not clear whether individual differences in cortical MD reflect neuroanatomical variability similarly detected by other MRI measures, or whether unique features are captured. For instance, variability in cortical MD may reflect morphological variability more commonly measured by cortical thickness. Differences among individuals in cortical MD may also arise from breakdowns in myelinated fibers running through the cortical mantle. Thus, we investigated whether genetic influences on variation in cortical MD are the same or different from those influencing cortical thickness and MD of white matter (WM) subjacent to the cortical ribbon. Univariate twin analyses indicated that cortical MD is heritable in the majority of brain regions; the average of regional heritability estimates ranged from 0.38 in the cingulate cortex to 0.66 in the occipital cortex, consistent with the heritability of other MRI measures of the brain. Trivariate analyses found that, while there was some shared genetic variance between cortical MD and each of the other two measures, this overlap was not complete (i.e., the correlation was statistically different from 1). A significant amount of distinct genetic variance influences inter-individual variability in cortical MD; therefore, this measure could be useful for further investigation in studies of neurodegenerative diseases and gene association studies., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Previous studies indicate that the microstructure of individual white matter (WM) tracts is related to cognitive function. More recent studies indicate that the microstructure of individual tracts is highly correlated and that a property common across WM is related to overall cognitive function in adults. However, little is known about whether these common WM properties exist in early childhood development or how they are related to cognitive development. In this study, we used diffusion tensor imaging (DTI) to investigate common underlying factors in 12 fiber tracts, their relationship with cognitive function, and their heritability in a longitudinal sample of healthy children at birth (n = 535), 1 y (n = 322), and 2 y (n = 244) of age. Our data show that, in neonates, there is a highly significant correlation between major WM tracts that decreases from birth to 2 y of age. Over the same period, the factor structure increases in complexity, from one factor at birth to three factors at age 2 y, which explain 50% of variance. The identified common factors of DTI metrics in each age group are significantly correlated with general cognitive scores and predict cognitive ability in later childhood. These factors are moderately heritable. These findings illustrate the anatomical differentiation of WM fiber from birth to 2 y of age that correlate with cognitive development. Our results also suggest that the common factor approach is an informative way to study WM development and its relationship with cognition and is a useful approach for future imaging genetic studies., Competing Interests: The authors declare no conflict of interest.

The precision of estimates in many statistical models can be expressed by a confidence interval (CI). CIs based on standard errors (SE) are common in practice, but likelihood-based CIs are worth consideration. In comparison to SEs, likelihood-based CIs are typically more difficult to estimate, but are more robust to model (re)parameterization. In latent variable models, some parameters may take on values outside of their interpretable range. Therefore, it is desirable to place a bound to keep the parameter interpretable. For likelihood-based CI, a correction is needed when a parameter is bounded. The correction is known (Wu & Neale, 2012), but is difficult to implement in practice. A novel automatic implementation that is simple for an applied researcher to use is introduced. A simulation study demonstrates the accuracy of the correction using a latent growth curve model and the method is illustrated with a multilevel confirmatory factor analysis.

Using Swedish nationwide registry data, the authors investigated the correlation of genetic and environmental risk factors in the etiology of drug abuse as ascertained from medical and criminal registries by modeling twin and sibling data. Medical drug abuse was defined using public inpatient and outpatient records, while criminal drug abuse was ascertained through legal records. Twin, full and half sibling pairs were obtained from the national twin and genealogical registers. Information about sibling pair residence within the same household was obtained from Statistics Sweden. Standard bivariate genetic structural equation modeling was applied to the population-based data on drug abuse ascertained through medical and crime registries, using OpenMx. Analyses of all possible pairs of twins (MZ: N = 4482; DZ: N = 9838 pairs), full- (N = 1,278,086) and half-siblings (paternal: N = 7767; maternal N = 70,553) who grew up together suggested that factors explaining familial resemblance for drug abuse as defined through medical or criminal registries were mostly the same. Results showed substantial heritability and moderate contributions of shared environmental factors to drug abuse; both were higher in males versus females, and higher for drug abuse ascertained through criminal than medical records. Because of the low prevalence of both assessments of drug abuse, having access to population data was crucial to obtain stable estimates. Using objective registry data, the authors found that drug abuse-whether ascertained through medical versus criminal records-was highly heritable. Furthermore, shared environmental factors contributed significantly to the liability of drug abuse. Genetic and shared environmental risk factors for these two forms of drug abuse were highly correlated.

White matter disease in the brain increases with age and cardiovascular disease, emerging in midlife, and these associations may be influenced by both genetic and environmental factors. We examined the frequency, distribution, and heritability of abnormal white matter and its association with hypertension in 395 middle-aged male twins (61.9 ± 2.6 years) from the Vietnam Era Twin Study of Aging, 67% of whom were hypertensive. A multi-channel segmentation approach estimated abnormal regions within the white matter. Using multivariable regression models, we characterized the frequency distribution of abnormal white matter in midlife and investigated associations with hypertension and Apolipoprotein E- ε4 status and the impact of duration and control of hypertension. Then, using the classical twin design, we estimated abnormal white matter heritability and the extent of shared genetic overlap with blood pressure. Abnormal white matter was predominantly located in periventricular and deep parietal and frontal regions; associated with age ( t  = 1.9, p  = 0.05) and hypertension ( t  = 2.9, p  = 0.004), but not Apolipoprotein ε4 status; and was greater in those with uncontrolled hypertension relative to controlled ( t  = 3.0, p  = 0.003) and normotensive ( t  = 4.0, p  = 0.0001) groups, suggesting that abnormal white matter may reflect currently active cerebrovascular effects. Abnormal white matter was highly heritable (a 2  = 0.81) and shared some genetic influences with systolic blood pressure (r A  = 0.26), although there was evidence for distinct genetic contributions and unique environmental influences. Future longitudinal research will shed light on factors impacting white matter disease presentation, progression, and potential recovery.

In the classical twin study, phenotypic variation is often partitioned into additive genetic (A), common (C) and specific environment (E) components. From genetical theory, the outcome of genotype by environment interaction is expected to inflate A when the interacting factor is shared (i.e., C) between the members of a twin pair. We show that estimates of both A and C can be inflated. When the shared interacting factor changes the size of the difference between homozygotes' means, the expected sibling or DZ twin correlation is .5 if and only if the minor allele frequency (MAF) is .5; otherwise the expected DZ correlation is greater than this value, consistent (and confounded) with some additional effect of C. This result is considered in the light of the distribution of minor allele frequencies for polygenic traits. Also discussed is whether such interactions take place at the locus level or affect an aggregated biological structure or system. Interactions with structures or endophenotypes that result from the aggregated effects of many loci will generally emerge as part of the A estimate.

Our aim was to test the direction of causation between self-report parental monitoring (PM) and the liability to illicit drug initiation (DI) as indicated by cannabis, cocaine, and stimulants. We fitted a multiple indicator model to test causal and non-causal models based on a large, genetically informative cross-sectional sample of male twins. The sample comprised 1,778 males aged 24-62 years from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders. Data came from self-report measures of lifetime cannabis, stimulants, and cocaine initiation, and retrospective assessment of PM between ages 8-17 years. Multivariate modeling showed that familial aggregation in PM and DI were both explained by a combination of additive genetic and shared environmental effects. Moreover, the significant association between PM and DI was best explained by a correlated liability model versus causal models. PM has typically been assumed to be an environmental, causal risk factor for drug use and has been shown to be among the more salient environmental risk factors for illicit DI. Our data were not consistent with this causal hypothesis. Instead, a correlated liability model in which PM and risk of DI share common genetic and environmental risks provided a better fit to the data.

The new software package OpenMx 2.0 for structural equation and other statistical modeling is introduced and its features are described. OpenMx is evolving in a modular direction and now allows a mix-and-match computational approach that separates model expectations from fit functions and optimizers. Major backend architectural improvements include a move to swappable open-source optimizers such as the newly written CSOLNP. Entire new methodologies such as item factor analysis and state space modeling have been implemented. New model expectation functions including support for the expression of models in LISREL syntax and a simplified multigroup expectation function are available. Ease-of-use improvements include helper functions to standardize model parameters and compute their Jacobian-based standard errors, access to model components through standard R $ mechanisms, and improved tab completion from within the R Graphical User Interface.

Maternal smoking during pregnancy (SDP) is associated with increased risk of externalizing and internalizing behaviors in offspring. Two explanations (not mutually exclusive) for this association are direct causal effects of maternal SDP and the effects of genetic and environmental factors common to parents and offspring which increase smoking as well as problem behaviors. Here, we examined the associations between parental SDP and mother rated offspring externalizing and internalizing behaviors (rated by the Child Behavior Checklist/2-3) at age three in a population-based sample of Dutch twins (N = 15,228 pairs). First, as a greater effect of maternal than of paternal SDP is consistent with a causal effect of maternal SDP, we compared the effects of maternal and paternal SDP. Second, as a beneficial effect of quitting smoking before pregnancy is consistent with the causal effect, we compared the effects of SDP in mothers who quit smoking before pregnancy, and mothers who continued to smoke during pregnancy. All mothers were established smokers before their pregnancy. The results indicated a greater effect of maternal SDP, compared to paternal SDP, for externalizing, aggression, overactive and withdrawn behavior. Quitting smoking was associated with less externalizing, overactive behavior, aggression, and oppositional behavior, but had no effect on internalizing, anxious depression, or withdrawn behavior. We conclude that these results are consistent with a causal, but small, effect of smoking on externalizing problems at age 3. The results do not support a causal effect of maternal SDP on internalizing behaviors.

Immune reconstitution kinetics and subsequent clinical outcomes in HLA-matched recipients of allogeneic stem cell transplantation (SCT) are variable and difficult to predict. Considering SCT as a dynamical system may allow sequence differences across the exomes of the transplant donors and recipients to be used to simulate an alloreactive T cell response, which may allow better clinical outcome prediction. To accomplish this, whole exome sequencing was performed on 34 HLA-matched SCT donor-recipient pairs (DRPs) and the nucleotide sequence differences translated to peptides. The binding affinity of the peptides to the relevant HLA in each DRP was determined. The resulting array of peptide-HLA binding affinity values in each patient was considered as an operator modifying a hypothetical T cell repertoire vector, in which each T cell clone proliferates in accordance with the logistic equation of growth. Using an iterating system of matrices, each simulated T cell clone's growth was calculated with the steady-state population being proportional to the magnitude of the binding affinity of the driving HLA-peptide complex. Incorporating competition between T cell clones responding to different HLA-peptide complexes reproduces a number of features of clinically observed T cell clonal repertoire in the simulated repertoire, including sigmoidal growth kinetics of individual T cell clones and overall repertoire, Power Law clonal frequency distribution, increase in repertoire complexity over time with increasing clonal diversity, and alteration of clonal dominance when a different antigen array is encountered, such as in SCT. The simulated, alloreactive T cell repertoire was markedly different in HLA-matched DRPs. The patterns were differentiated by rate of growth and steady-state magnitude of the simulated T cell repertoire and demonstrate a possible correlation with survival. In conclusion, exome wide sequence differences in DRPs may allow simulation of donor alloreactive T cell response to recipient antigens and may provide a quantitative basis for refining donor selection and titration of immunosuppression after SCT., (Copyright © 2016 American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.)

Depression is a highly heterogeneous condition, and identifying how symptoms present in various groups may greatly increase our understanding of its etiology. Importantly, Major Depressive Disorder is strongly linked with Substance Use Disorders, which may ameliorate or exacerbate specific depression symptoms. It is therefore quite plausible that depression may present with different symptom profiles depending on an individual's substance use status. Given these observations, it is important to examine the underlying construct of depression in groups of substance users compared to non-users. In this study we use a non-clinical sample to examine the measurement structure of the Beck Depression Inventory (BDI-II) in non-users and frequent-users of various substances. Specifically, measurement invariance was examined across those who do vs. do not use alcohol, nicotine, and cannabis. Results indicate strict factorial invariance across non-users and frequent-users of alcohol and cannabis, and metric invariance across non-users and frequent-users of nicotine. This implies that the factor structure of the BDI-II is similar across all substance use groups.

Objective: We examined the association between the genetic and environmental factors contributing to the liability to having ever engaged in self-induced vomiting (SIV initiation) and the genetic and environmental factors contributing to regular SIV behaviors (weekly or daily) for weight control., Method: SIV was assessed in 3,942 women from monozygotic twin pairs and 2,790 women from same-sex dizygotic twin pairs, aged 20-47, from the Swedish Twin study of Adults: Genes and Environment. A causal-contingent-common pathway model assessed the extent to which genetic and environmental factors that influence initiation of SIV also influence regular SIV behaviors., Results: In the best-fit model, genetic and individual-specific environmental factors influenced liability to SIV initiation. The genetic factors influencing regular SIV behaviors were the same as the genetic factors influencing SIV initiation. Additional individual-specific environmental factors that were unrelated to SIV initiation influenced regular SIV behaviors., Discussion: Our findings provide evidence that the underlying liabilities for SIV initiation and regular SIV lie on the same continuum given the degree of overlap in risk between SIV initiation and regular SIV behaviors. Further, the lack of specific genetic factors and the importance of individual-specific environmental factors for regular SIV behaviors highlight the significance of environmental factors in the etiology of eating disorder symptomatology and the non-deterministic nature of genetic factors. Finally, our results suggest that when it comes to preventing individuals from developing regular SIV behavior, intervening at an environmental level is warranted., (© 2015 Wiley Periodicals, Inc.)

General cognitive ability (GCA) has substantial explanatory power for behavioral and health outcomes, but its cortical substrate is still not fully established. GCA is highly polygenic and research to date strongly suggests that its cortical substrate is highly polyregional. We show in map-based and region-of-interest-based analyses of adult twins that a complex cortical configuration underlies GCA. Having relatively greater surface area in evolutionary and developmentally high-expanded prefrontal, lateral temporal, and inferior parietal regions is positively correlated with GCA, whereas relatively greater surface area in low-expanded occipital, medial temporal, and motor cortices is negatively correlated with GCA. Essentially the opposite pattern holds for relative cortical thickness. The phenotypic positive-to-negative gradients in our cortical-GCA association maps were largely driven by a similar pattern of genetic associations. The patterns are consistent with regional cortical stretching whereby relatively greater surface area is related to relatively thinner cortex in high-expanded regions. Thus, the typical "bigger is better" view does not adequately capture cortical-GCA associations. Rather, cognitive ability is influenced by complex configurations of cortical development patterns that are strongly influenced by genetic factors. Optimal cognitive ability appears to be driven both by the absolute size and the polyregional configuration of the entire cortex rather than by small, circumscribed regions., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The mu1 opioid receptor gene, OPRM1, has long been a high-priority candidate for human genetic studies of addiction. Because of its potential functional significance, the non-synonymous variant rs1799971 (A118G, Asn40Asp) in OPRM1 has been extensively studied, yet its role in addiction has remained unclear, with conflicting association findings. To resolve the question of what effect, if any, rs1799971 has on substance dependence risk, we conducted collaborative meta-analyses of 25 datasets with over 28,000 European-ancestry subjects. We investigated non-specific risk for "general" substance dependence, comparing cases dependent on any substance to controls who were non-dependent on all assessed substances. We also examined five specific substance dependence diagnoses: DSM-IV alcohol, opioid, cannabis, and cocaine dependence, and nicotine dependence defined by the proxy of heavy/light smoking (cigarettes-per-day >20 vs. ≤ 10). The G allele showed a modest protective effect on general substance dependence (OR = 0.90, 95% C.I. [0.83-0.97], p value = 0.0095, N = 16,908). We observed similar effects for each individual substance, although these were not statistically significant, likely because of reduced sample sizes. We conclude that rs1799971 contributes to mechanisms of addiction liability that are shared across different addictive substances. This project highlights the benefits of examining addictive behaviors collectively and the power of collaborative data sharing and meta-analyses.

Background: Obsessive-compulsive disorder (OCD) is characterized by five major dimensions, including contamination/washing, harm/checking, symmetry/ordering, hoarding, and forbidden thoughts. How these dimensions may relate etiologically to the symptoms of other obsessive-compulsive related disorders (OCRDs) and anxiety disorders (ADs) is not well known. The aim of this study was to examine the genetic and environmental overlap between each major obsessive-compulsive dimension with the symptoms of other OCRDs and ADs., Methods: Two thousand four hundred ninety-five twins of both sexes, aged between 18 and 45 years, were recruited from the Australian Twin Registry. Measures used scores on four dimensions (obsessing (forbidden thoughts), washing, checking, and ordering) of the Obsessive-Compulsive Inventory-Revised, Dysmorphic Concerns Questionnaire, Hoarding Rating Scale, Anxiety Sensitivity Index, Social Phobia Inventory, and Stress subscale of the Depression, Anxiety, and Stress Scale. Multivariate twin modeling methods using continuous and categorized variables were performed, also controlling for age and gender., Results: Our findings suggested that forbidden thoughts and washing demonstrated the strongest genetic overlap with other AD symptoms, while ordering was genetically related to OCRD symptoms. Common genetic influences on checking symptoms were best estimated when modeling OCRDs together with AD symptoms. Common environmental factors of ordering and checking were shared with AD symptoms., Conclusions: Important shared genetic and environmental risk factors exist between OCD, OCRDs, and ADs, but which vary alongside the expression of its major dimensions., (© 2015 Wiley Periodicals, Inc.)

Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders.

A linear latent growth curve mixture model with regime switching is extended in 2 ways. Previously, the matrix of first-order Markov switching probabilities was specified to be time-invariant, regardless of the pair of occasions being considered. The first extension, time-varying transitions, specifies different Markov transition matrices between each pair of occasions. The second extension is second-order time-invariant Markov transition probabilities, such that the probability of switching depends on the states at the 2 previous occasions. The models are implemented using the R package OpenMx, which facilitates data handling, parallel computation, and further model development. It also enables the extraction and display of relative likelihoods for every individual in the sample. The models are illustrated with previously published data on alcohol use observed on 4 occasions as part of the National Longitudinal Survey of Youth, and demonstrate improved fit to the data.

We present a novel method of conducting biometric analysis of twin data when the phenotypes are integer-valued counts, which often show an L-shaped distribution. Monte Carlo simulation is used to compare five likelihood-based approaches to modeling: our multivariate discrete method, when its distributional assumptions are correct, when they are incorrect, and three other methods in common use. With data simulated from a skewed discrete distribution, recovery of twin correlations and proportions of additive genetic and common environment variance was generally poor for the Normal, Lognormal and Ordinal models, but good for the two discrete models. Sex-separate applications to substance-use data from twins in the Minnesota Twin Family Study showed superior performance of two discrete models. The new methods are implemented using R and OpenMx and are freely available.

Aims: This study explored the factor structure of DSM III-R/IV symptoms for substance abuse and dependence across six illicit substance categories in a population-based sample of males., Method: DSM III-R/IV drug abuse and dependence symptoms for cannabis, sedatives, stimulants, cocaine, opioids and hallucinogens from 4179 males born 1940-1970 from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders were analyzed. Confirmatory factor analyses tested specific hypotheses regarding the latent structure of substance misuse for a comprehensive battery of 13 misuse symptoms measured across six illicit substance categories (78 items)., Results: Among the models fit, the latent structure of substance misuse was best represented by a combination of substance-specific factors and misuse symptom-specific factors. We found no support for a general liability factor to illicit substance misuse., Conclusions: Results indicate that liability to misuse illicit substances is drug class specific, with little evidence for a general liability factor. Additionally, unique dimensions capturing propensity toward specific misuse symptoms (e.g., tolerance, withdrawal) across substances were identified. While this finding requires independent replication, the possibility of symptom-specific misuse factors, present in multiple substances, raises the prospect of genetic, neurobiological and behavioral predispositions toward distinct, narrowly defined features of drug abuse and dependence., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Excessive internet use has been linked to psychopathology. Therefore, understanding the genetic and environmental risks underpinning internet use and their relation to psychopathology is important. This study aims to explore the genetic and environmental etiology of internet use measures and their associations with internalizing disorders and substance use disorders. The sample included 2,059 monozygotic (MZ) and dizygotic (DZ) young adult twins from the Brisbane Longitudinal Twin Study (BLTS). Younger participants reported more frequent internet use, while women were more likely to use the internet for interpersonal communication. Familial aggregation in 'frequency of internet use' was entirely explained by additive genetic factors accounting for 41% of the variance. Familial aggregation in 'frequency of use after 11 pm', 'using the internet to contact peers', and 'using the internet primarily to access social networking sites' was attributable to varying combinations of additive genetic and shared environmental factors. In terms of psychopathology, there were no significant associations between internet use measures and major depression (MD), but there were positive significant associations between 'frequency of internet use' and 'frequency of use after 11 pm' with social phobia (SP). 'Using the internet to contact peers' was positively associated with alcohol abuse, whereas 'using the internet to contact peers' and 'using the internet primarily to access social networking sites' were negatively associated with cannabis use disorders and nicotine symptoms. Individual differences in internet use can be attributable to varying degrees of genetic and environmental risks. Despite some significant associations of small effect, variation in internet use appears mostly unrelated to psychopathology.

Background: There is substantial comorbidity between personality disorders (PDs) and anxiety disorders (ADs). Sharing of familial risk factors possibly explains the co-occurrence, but direct causal relationships between the disorders may also exist., Methods: 2801 persons from 1391 twin pairs from the Norwegian Institute of Public Health Twin Panel were assessed for all DSM-IV PDs and ADs. Bivariate Poisson-regression analyses were performed to assess whether PDs predicted ADs at three different levels: All PDs combined, PDs combined within DSM-IV-clusters and each individual PD separately. Next, bivariate co-twin control analyses were executed within monozygotic (MZ) and dizygotic (DZ) twin pairs. A similar analytic strategy was employed in multivariate models including PDs as independent variables., Results: PDs predicted ADs at all levels of analysis in bivariate regression models. Bivariate co-twin control analyses demonstrated an increased risk of ADs in all PDs combined, all PD-clusters and in schizotypal, paranoid, borderline, antisocial, avoidant and dependent PD. In the multivariate regression model, all PD-clusters and schizotypal, borderline, avoidant and obsessive-compulsive PD predicted ADs. Only borderline and avoidant PD predicted ADs in the multivariate co-twin control analysis., Limitations: Over-adjustment may explain the results from the multivariate analyses. The cross-sectional study design hampers causal inference., Conclusions: Comorbidity between ADs and PDs can be largely accounted for by shared familial risk factors. However, the results are also consistent with a direct causal relationship partly explaining the co-occurrence. Our results indicate specific environmental factors for comorbidity of ADs and borderline and avoidant PDs that are not shared with other PDs., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Reliability has a long history as one of the key psychometric properties of a test. However, a given test might not measure people equally reliably. Test scores from some individuals may have considerably greater error than others. This study proposed two approaches using intraindividual variation to estimate test reliability for each person. A simulation study suggested that the parallel tests approach and the structural equation modeling approach recovered the simulated reliability coefficients. Then in an empirical study, where forty-five females were measured daily on the Positive and Negative Affect Schedule (PANAS) for 45 consecutive days, separate estimates of reliability were generated for each person. Results showed that reliability estimates of the PANAS varied substantially from person to person. The methods provided in this article apply to tests measuring changeable attributes and require repeated measures across time on each individual. This article also provides a set of parallel forms of PANAS.

Borderline personality disorder (BPD) is a barrier to treatment, yet the relationship between BPD features and other psychopathology symptoms in residential addictions treatment samples is understudied. Using a sample of adults enrolled in a residential drug treatment facility measured at baseline and 2-3 month follow-up, the authors examined the prospective relationship between BPD features and five indices of psychopathology: depression, anxiety, interpersonal sensitivity, hostility, and psychoticism, as well as psychopathology global severity. There was no effect of time on any of the forms of psychopathology, but females reported higher levels of BPD features, anxiety symptoms, and interpersonal sensitivity than males. A series of latent change score models indicated that BPD features predicted increases in all psychopathology scales at follow-up, while the reverse was not true. These results suggest that targeting BPD features in residents of drug treatment facilities may reduce the emergence of new psychopathology in the short term.

Background: Mixed anxiety-depression (MAD) has been under scrutiny to determine its potential place in psychiatric nosology. The current study sought to investigate its prevalence, clinical characteristics, course and potential validators., Method: Restricted latent-class analyses were fit to 12-month self-reports of depression and anxiety symptom criteria in a large population-based sample of twins. Classes were examined across an array of relevant indicators (demographics, co-morbidity, adverse life events, clinical significance and twin concordance). Longitudinal analyses investigated the stability of, and transitions between, these classes for two time periods approximately 1.5 years apart., Results: In all analyses, a class exhibiting levels of MAD symptomatology distinctly above the unaffected subjects yet having low prevalence of either major depression (MD) or generalized anxiety disorder (GAD) was identified. A restricted four-class model, constraining two classes to have no prior disorder history to distinguish residual or recurrent symptoms from new onsets in the last year, provided an interpretable classification: two groups with no prior history that were unaffected or had MAD and two with prior history having relatively low or high symptom levels. Prevalence of MAD was substantial (9-11%), and subjects with MAD differed quantitatively but not qualitatively from those with lifetime MD or GAD across the clinical validators examined., Conclusions: Our findings suggest that MAD is a commonly occurring, identifiable syndromal subtype that warrants further study and consideration for inclusion in future nosologic systems.

Background: Antisocial personality disorder (ASPD) and borderline personality disorder (BPD) share genetic and environmental risk factors. Little is known about the temporal stability of these etiological factors in adulthood., Method: DSM-IV criteria for ASPD and BPD were assessed using structured interviews in 2282 Norwegian twins in early adulthood and again approximately 10 years later. Longitudinal biometric models were used to analyze the number of endorsed criteria., Results: The mean criterion count for ASPD and BPD decreased 40% and 28%, respectively, from early to middle adulthood. Rank-order stability was 0.58 for ASPD and 0.45 for BPD. The best-fitting longitudinal twin model included only genetic and individual-specific environmental factors. Genetic effects, both those shared by ASPD and BPD, and those specific to each disorder remained completely stable. The unique environmental effects, however, changed substantially, with a correlation across time of 0.19 for the shared effects, and 0.39 and 0.15, respectively, for those specific to ASPD and BPD. Genetic effects accounted for 71% and 72% of the stability over time for ASPD and BPD, respectively. The genetic and environmental correlations between ASPD and BPD were 0.73, and 0.43, respectively, at both time points., Conclusion: ASPD and BPD traits were moderately stable from early to middle adulthood, mostly due to genetic risk factors which did not change over the 10-year assessment period. Environmental risk factors were mostly transient, and appear to be the main source of phenotypic change. Genetic liability factors were, to a large extent, shared by ASPD and BPD.

Background: Most twin studies of multiple sclerosis (MS) are inconclusive regarding the impact of genes and environment on disease susceptibility. In particular, high uncertainty exists about whether shared environmental factors are aetiologically relevant., Objective: To disentangle, with a reasonable degree of confidence, the relative contributions of heritability and of shared and unique environmental components of MS susceptibility., Methods: We performed a meta-analysis of previous twin studies. After a MEDLINE search, we selected eight twin studies in France, UK, Canada, Denmark, North America, Italy, Finland and Sweden. We conducted a biometric multi-group analysis under the liability-threshold model, by taking account of the study-specific ascertainment strategies and the population-specific prevalence rates of MS., Results: The meta-analytic estimates of tetrachoric correlations were 0.71 (95% confidence interval (CI): 0.67-0.74) in monozygotic pairs and 0.46 (95% CI: 0.41-0.50) in dizygotic pairs. The biometric multi-group model provided meta-analytic estimates of 0.50 (95% CI: 0.39-0.61) for heritability, 0.21 (95% CI: 0.11-0.30) for shared environmental component and 0.29 (95% CI: 0.26-0.33) for unique environmental component., Conclusion: Our results support the continuing efforts to identify unknown genetic factors that fill the gap of 'missing heritability'; moreover, a 'missing environmentality' deserves future investigations into the role of non-heritable components that act as both shared and individual-specific exposures., (© The Author(s), 2015.)

We examined network properties of genetic covariance between average cortical thickness (CT) and surface area (SA) within genetically-identified cortical parcellations that we previously derived from human cortical genetic maps using vertex-wise fuzzy clustering analysis with high spatial resolution. There were 24 hierarchical parcellations based on vertex-wise CT and 24 based on vertex-wise SA expansion/contraction; in both cases the 12 parcellations per hemisphere were largely symmetrical. We utilized three techniques-biometrical genetic modeling, cluster analysis, and graph theory-to examine genetic relationships and network properties within and between the 48 parcellation measures. Biometrical modeling indicated significant shared genetic covariance between size of several of the genetic parcellations. Cluster analysis suggested small distinct groupings of genetic covariance; networks highlighted several significant negative and positive genetic correlations between bilateral parcellations. Graph theoretical analysis suggested that small world, but not rich club, network properties may characterize the genetic relationships between these regional size measures. These findings suggest that cortical genetic parcellations exhibit short characteristic path lengths across a broad network of connections. This property may be protective against network failure. In contrast, previous research with structural data has observed strong rich club properties with tightly interconnected hub networks. Future studies of these genetic networks might provide powerful phenotypes for genetic studies of normal and pathological brain development, aging, and function.

Total gray matter volume is associated with general cognitive ability (GCA), an association mediated by genetic factors. It is expectable that total neocortical volume should be similarly associated with GCA. Neocortical volume is the product of thickness and surface area, but global thickness and surface area are unrelated phenotypically and genetically in humans. The nature of the genetic association between GCA and either of these 2 cortical dimensions has not been examined. Humans possess greater cognitive capacity than other species, and surface area increases appear to be the primary driver of the increased size of the human cortex. Thus, we expected neocortical surface area to be more strongly associated with cognition than thickness. Using multivariate genetic analysis in 515 middle-aged twins, we demonstrated that both the phenotypic and genetic associations between neocortical volume and GCA are driven primarily by surface area rather than thickness. Results were generally similar for each of 4 specific cognitive abilities that comprised the GCA measure. Our results suggest that emphasis on neocortical surface area, rather than thickness, could be more fruitful for elucidating neocortical-GCA associations and identifying specific genes underlying those associations., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Objective: Negative urgency (NU; tendency to act impulsively when experiencing negative emotions) is a risk factor for binge eating, although few studies have examined interviewer-assessed objective binge episodes (OBEs). Moreover, research has not investigated how NU relates to the core components of OBEs: loss of control (LOC) eating and objective overeating (OO). Understanding the relationship between NU and these core components will enhance etiologic models of eating disorder development. Thus, the current study examined the associations between NU, OBEs, and the components of OBEs by comparing levels of NU in women with OBEs, LOC eating only, and OO only to women with no pathological eating., Method: Participants were 612 women who endorsed lifetime OBEs (5.4%), LOC eating outside of OBEs (5.7%), OO only (2.8%), or none of these eating episodes (85.9%)., Results: Women with OBEs, LOC only, and OO only had significantly higher levels of NU than women without these episodes, suggesting that NU is associated with both the LOC and OO components of OBEs., Discussion: NU relates to the spectrum of pathology present in women with OBEs. Future research should examine the mechanisms underlying these associations, including impaired behavioral/psychological control and/or increased reward sensitivity in response to negative affect., (© 2015 Wiley Periodicals, Inc.)

Systems that evolve over time and follow mathematical laws as they evolve are called dynamical systems. Lymphocyte recovery and clinical outcomes in 41 allograft recipients conditioned using antithymocyte globulin (ATG) and 4.5-Gy total body irradiation were studied to determine if immune reconstitution could be described as a dynamical system. Survival, relapse, and graft-versus-host disease (GVHD) were not significantly different in 2 cohorts of patients receiving different doses of ATG. However, donor-derived CD3(+) cell reconstitution was superior in the lower ATG dose cohort, and there were fewer instances of donor lymphocyte infusion (DLI). Lymphoid recovery was plotted in each individual over time and demonstrated 1 of 3 sigmoid growth patterns: Pattern A (n = 15) had rapid growth with high lymphocyte counts, pattern B (n = 14) had slower growth with intermediate recovery, and pattern C (n = 10) had poor lymphocyte reconstitution. There was a significant association between lymphocyte recovery patterns and both the rate of change of donor-derived CD3(+) at day 30 after stem cell transplantation (SCT) and clinical outcomes. GVHD was observed more frequently with pattern A, relapse and DLI more so with pattern C, with a consequent survival advantage in patients with patterns A and B. We conclude that evaluating immune reconstitution after SCT as a dynamical system may differentiate patients at risk of adverse outcomes and allow early intervention to modulate that risk., (Copyright © 2015 American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.)

This study explores power assumptions relating to extended pedigree designs (EPD) and classical twin designs (CTD). We conducted statistical analyses to compare the power of the two designs for examining neuroimaging phenotypes, varying heritability and varying whether shared environmental variance is fixed or free. Results indicated that CTDs have more power to estimate heritability, with the exception of one condition: in EPDs, the power increases relative to CTDs when shared environmental variance contributes to sibling similarity only. We additionally show that assuming a priori that shared environmental effects play no role in a phenotype-as is commonly done in pedigree designs-can lead to substantially biased heritability estimates. General results indicate that both CTDs and EPDs obtain quite precise heritability estimates. Finally, we discuss methodological considerations relating to assumptions about age effects and shared environment.

Episodic memory is a complex construct at both the phenotypic and genetic level. Ample evidence supports age-related cognitive stability and change being accounted for by general and domain-specific factors. We hypothesized that general and specific factors would underlie change even within this single cognitive domain. We examined 6 measures from 3 episodic memory tests in a narrow age cohort at middle and late middle age. The factor structure was invariant across occasions. At both timepoints 2 of 3 test-specific factors (story recall, design recall) had significant genetic influences independent of the general memory factor. Phenotypic stability was moderate to high, and primarily accounted for by genetic influences, except for 1 test-specific factor (list learning). Mean change over time was nonsignificant for 1 test-level factor; 1 declined; 1 improved. The results highlight the phenotypic and genetic complexity of memory and memory change, and shed light on an understudied period of life., ((c) 2015 APA, all rights reserved.)

Empirically derived phenotypic measurements have the potential to enhance gene-finding efforts in schizophrenia. Previous research based on factor analyses of symptoms has typically included schizoaffective cases. Deriving factor loadings from analysis of only narrowly defined schizophrenia cases could yield more sensitive factor scores for gene pathway and gene ontology analyses. Using an Irish family sample, this study 1) factor analyzed clinician-rated Operational Criteria Checklist items in cases with schizophrenia only, 2) scored the full sample based on these factor loadings, and 3) implemented genome-wide association, gene-based, and gene-pathway analysis of these SCZ-based symptom factors (final N=507). Three factors emerged from the analysis of the schizophrenia cases: a manic, a depressive, and a positive symptom factor. In gene-based analyses of these factors, multiple genes had q<0.01. Of particular interest are findings for PTPRG and WBP1L, both of which were previously implicated by the Psychiatric Genomics Consortium study of SCZ; results from this study suggest that variants in these genes might also act as modifiers of SCZ symptoms. Gene pathway analyses of the first factor indicated over-representation of glutamatergic transmission, GABA-A receptor, and cyclic GMP pathways. Results suggest that these pathways may have differential influence on affective symptom presentation in schizophrenia., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Objective: In an effort to address earliest detection of mild cognitive impairment (MCI), we examined hippocampal volumes and atrophy in middle-aged men to explore neuroanatomical support for different neuropsychological definitions of MCI., Methods: 460 men aged 51-60 years underwent neuropsychological testing and MRI. MCI was defined according to five criteria sets. MRI-derived hippocampal volume and hippocampal occupancy (HOC) were obtained via FreeSurfer. Statistical analyses were performed using linear mixed models., Results: Differences in HOC between normal cognitive functioning, amnestic, and non-amnestic MCI were observed using MCI criteria that required one impaired (>1.5 SD) cognitive measure in a given cognitive domain or a cognitive composite score method with a cut-point 2 SD below the mean. Differences in standard hippocampal volume were only found between normal and amnestic presentations and only when using the composite score method., Conclusion: Results provide empirical support for detection of pre-MCI in younger cohorts. Convergence of neuropsychological and neuroanatomical data, particularly HOC (as opposed to standard cross-sectional volume), supports early identification of MCI as defined by some neuropsychological criteria., (Published by Elsevier Inc.)

Background: While cluster A personality disorders (PDs) have been shown to be moderately heritable, we know little about the temporal stability of these genetic risk factors., Method: Paranoid PD (PPD) and schizotypal PD (STPD) were assessed using the Structured Interview for DSM-IV Personality in 2793 young adult twins from the Norwegian Institute of Public Health Twin Panel at wave 1 and 2282 twins on average 10 years later at wave 2. Using the program Mx, we fitted a longitudinal latent factor model using the number of endorsed criteria for PPD and STPD., Results: The stability over time of the criteria counts for PPD and STPD, estimated as polychoric correlations, were +0.34 and +0.40, respectively. The best-fit longitudinal model included only additive genetic and individual-specific environmental factors with parameter estimates constrained to equality across the two waves. The cross-wave genetic and individual-specific environmental correlations for a latent cluster A factor were estimated to equal +1.00 and +0.13, respectively. The cross-time correlations for genetic and environmental effects specific to the individual PDs were estimated at +1.00 and +0.16-0.20, respectively. We found that 68% and 71% of the temporal stability of PPD and STPD derived, respectively, from the effect of genetic factors., Conclusion: Shared genetic risk factors for two of the cluster A PDs are highly stable in adults over a 10-year period while environmental risk factors are relatively transient. Over two-thirds of the long-term stability of the common cluster A PD liability can be attributed to genetic influences.

Studies in adults indicate that white matter microstructure, assessed with diffusion tensor imaging (DTI), has high heritability. Little is known about genetic and environmental influences on DTI parameters, measured along fiber tracts particularly, in early childhood. In the present study, we report comprehensive heritability data of white matter microstructure fractional anisotropy (FA), radial diffusion (RD), and axial diffusion (AD) along 47 fiber tracts using the quantitative tractography in a large sample of neonatal twins (n=356). We found significant genetic influences in almost all tracts with similar heritabilities for FA, RD, and AD as well as positive relationships between these parameters and heritability. In a single tract analysis, genetic influences along the length of the tract were highly variable. These findings suggest that at birth, there is marked heterogeneity of genetic influences of white matter microstructure within white matter tracts. This study provides a basis for future studies of developmental changes in genetic and environmental influences during early childhood, a period of rapid development that likely plays a major role in individual differences in white matter structure and function., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Background: To clarify the role of genetic and environmental risk factors in alcohol use disorders (AUDs), we performed a meta-analysis of twin and adoption studies and explored the impact of sex, assessment method (interview v. hospital/population records), and study design (twin v. adoption study) on heritability estimates., Method: The literature was searched for all unique twin and adoption studies of AUD and identified 12 twin and five adoption studies. The data were then reconstructed and analyzed using ordinal data full information maximum likelihood in the OpenMx program. Heterogeneity was tested with likelihood ratio tests by equating the parameters across studies., Results: There was no evidence for heterogeneity by study design, sex or assessment method. The best-fit estimate of the heritability of AUD was 0.49 [95% confidence interval (CI) 0.43-0.53], and the proportion of shared environmental variance was 0.10 (95% CI 0.03-0.16). Estimates of unique environmental proportions of variance differed significantly across studies., Conclusions: AUD is approximately 50% heritable. The multiple genetically informative studies of this syndrome have produced consistent results that support the validity of this heritability estimate, especially given the different potential methodological weaknesses of twin and adoption designs, and of assessments of AUD based on personal interviews v. official records. We also found evidence for modest shared environmental effects suggesting that environmental factors also contribute to the familial aggregation of AUDs.

Chronic cigarette use has been consistently associated with differences in the neuroanatomy of smokers relative to nonsmokers in case-control studies. However, the etiology underlying the relationships between brain structure and cigarette use is unclear. A community-based sample of male twin pairs ages 51-59 (110 monozygotic pairs, 92 dizygotic pairs) was used to determine the extent to which there are common genetic and environmental influences between brain structure and average lifetime cigarette use. Brain structure was measured by high-resolution structural magnetic resonance imaging, from which subcortical volume and cortical volume, thickness and surface area were derived. Bivariate genetic models were fitted between these measures and average lifetime cigarette use measured as cigarette pack-years. Widespread, negative phenotypic correlations were detected between cigarette pack-years and several cortical as well as subcortical structures. Shared genetic and unique environmental factors contributed to the phenotypic correlations shared between cigarette pack-years and subcortical volume as well as cortical volume and surface area. Brain structures involved in many of the correlations were previously reported to play a role in specific aspects of networks of smoking-related behaviors. These results provide evidence for conducting future research on the etiology of smoking-related behaviors using measures of brain morphology.

The phenotypic and genetic relationship between global cortical size and general cognitive ability (GCA) appears to be driven by surface area (SA) and not cortical thickness (CT). Gyrification (cortical folding) is an important property of the cortex that helps to increase SA within a finite space, and may also improve connectivity by reducing distance between regions. Hence, gyrification may be what underlies the SA-GCA relationship. In previous phenotypic studies, a 3-dimensional gyrification index (3DGI) has been positively associated with cognitive ability and negatively associated with mild cognitive impairment, Alzheimer's disease, and psychiatric disorders affecting cognition. However, the differential genetic associations of 3DGI and SA with GCA are still unclear. We examined the heritability of 3DGI, and the phenotypic, genetic, and environmental associations of 3DGI with SA and GCA in a large sample of adult male twins (N = 512). Nearly 85% of the variance in 3DGI was due to genes, and 3DGI had a strong phenotypic and genetic association with SA. Both 3DGI and total SA had positive phenotypic correlations with GCA. However, the SA-GCA correlation remained significant after controlling for 3DGI, but not the other way around. There was also significant genetic covariance between SA and GCA, but not between 3DGI and GCA. Thus, despite the phenotypic and genetic associations between 3DGI and SA, our results do not support the hypothesis that gyrification underlies the association between SA and GCA., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Prenatal testosterone exposure may be protective against disordered eating. However, prior studies have produced mixed results. Developmental differences in prenatal testosterone's protective effects on disordered eating may explain these discrepancies. Indeed, studies have differed in the age of participants assessed, with data supporting prenatal testosterone effects on disordered eating in early adolescent and young adult samples but not in late adolescence. The present studies are the first to investigate age differences in prenatal testosterone's protective effects on disordered eating. Two indirect markers of higher prenatal testosterone were examined: (a) lower finger-length ratios (Study 1: index [2D]/ring [4D] finger [2D:4D]) and (b) lower disordered eating in female s from opposite-sex twin pairs (who are thought to be exposed to higher prenatal testosterone from their male co-twin) relative to female controls (Study 2). Participants were twins from the Michigan State University Twin Registry (Study 1: n = 409; Study 2: n = 1,538) in early adolescence, late adolescence, or young adulthood. Disordered eating was assessed with well-validated questionnaires. Finger-length ratios were measured from hand scans, using electronic computer calipers. Findings were consistent across both studies. Higher prenatal testosterone (lower 2D:4D; females from opposite-sex twin pairs vs. controls) predicted lower disordered eating in early adolescence and young adulthood only. Prenatal testosterone-disordered eating associations were not observed during late adolescence. Results point to the possibility of developmental windows of expression for prenatal testosterone's protective effects on disordered eating and suggest that prior discrepant results may reflect age differences across samples., (PsycINFO Database Record (c) 2015 APA, all rights reserved.)

Maintained Individual Data Distributed Likelihood Estimation (MIDDLE) is a novel paradigm for research in the behavioral, social, and health sciences. The MIDDLE approach is based on the seemingly impossible idea that data can be privately maintained by participants and never revealed to researchers, while still enabling statistical models to be fit and scientific hypotheses tested. MIDDLE rests on the assumption that participant data should belong to, be controlled by, and remain in the possession of the participants themselves. Distributed likelihood estimation refers to fitting statistical models by sending an objective function and vector of parameters to each participant's personal device (e.g., smartphone, tablet, computer), where the likelihood of that individual's data is calculated locally. Only the likelihood value is returned to the central optimizer. The optimizer aggregates likelihood values from responding participants and chooses new vectors of parameters until the model converges. A MIDDLE study provides significantly greater privacy for participants, automatic management of opt-in and opt-out consent, lower cost for the researcher and funding institute, and faster determination of results. Furthermore, if a participant opts into several studies simultaneously and opts into data sharing, these studies automatically have access to individual-level longitudinal data linked across all studies.

Outcomes in stem cell transplantation (SCT) are modeled using probability theory. However, the clinical course following SCT appears to demonstrate many characteristics of dynamical systems, especially when outcomes are considered in the context of immune reconstitution. Dynamical systems tend to evolve over time according to mathematically determined rules. Characteristically, the future states of the system are predicated on the states preceding them, and there is sensitivity to initial conditions. In SCT, the interaction between donor T cells and the recipient may be considered as such a system in which, graft source, conditioning, and early immunosuppression profoundly influence immune reconstitution over time. This eventually determines clinical outcomes, either the emergence of tolerance or the development of graft versus host disease. In this paper, parallels between SCT and dynamical systems are explored and a conceptual framework for developing mathematical models to understand disparate transplant outcomes is proposed.

While many studies have reported that individual differences in personality traits are genetically influenced, the neurobiological bases mediating these influences have not yet been well characterized. To advance understanding concerning the pathway from genetic variation to personality, here we examined whether measures of heritable variation in neuroanatomical size in candidate regions (amygdala and medial orbitofrontal cortex) were associated with heritable effects on personality. A sample of 486 middle-aged (mean=55 years) male twins (complete MZ pairs=120; complete DZ pairs=84) underwent structural brain scans and also completed measures of two core domains of personality: positive and negative emotionality. After adjusting for estimated intracranial volume, significant phenotypic (r(p)) and genetic (r(g)) correlations were observed between left amygdala volume and positive emotionality (r(p)=.16, p<.01; r(g)=.23, p<.05, respectively). In addition, after adjusting for mean cortical thickness, genetic and nonshared-environmental correlations (r(e)) between left medial orbitofrontal cortex thickness and negative emotionality were also observed (r(g)=.34, p<.01; r(e)=-.19, p<.05, respectively). These findings support a model positing that heritable bases of personality are, at least in part, mediated through individual differences in the size of brain structures, although further work is still required to confirm this causal interpretation., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Individuals with obsessive compulsive disorder can display diverse and heterogeneous patterns of symptoms. Little is known about the relationship between obsessive-compulsive symptom (OCS) dimensions and normal personality traits, particularly those that increase risk for other internalizing disorders. In this study of 1,382 individuals from female-female twin pairs, we examined the relationship between self-report OCS dimensions derived from the Padua Inventory and Eysenck's personality traits neuroticism and extraversion. We conducted factor analysis to determine their phenotypic structure followed by twin analyses to determine their genetic and environmental sources of covariation. A three-factor solution, with dimensions corresponding to checking, aggressive obsessions, and contamination, was the best fit for the Padua OCS items. These dimensions were significantly and somewhat variably associated with neuroticism but negligibly associated with extraversion. The genetic correlations between neuroticism and these three OCS dimensions were moderate to high (0.66 with checking, 0.89 with aggressive obsessions, and 0.40 with contamination). However, the estimated genetic correlation between neuroticism and a unified latent OCS construct was smaller (0.32). Overall this study suggests that genetic, and to a smaller extent environmental, factors underlying neuroticism may act differentially as risk factors for OCS dimensions., (© 2014 Wiley Periodicals, Inc.)