Evidence of shared familial factors influencing neurocognitive endophenotypes in adult- and childhood-onset schizophrenia.

BACKGROUND: The aggregation of neurocognitive deficits among the non-psychotic first-degree relatives of adult- and childhood-onset schizophrenia patients suggests that there may be a common etiology for these deficits in childhood- and adult-onset illness. However, there is considerable heterogeneity in the presentation of neurobiological abnormalities, and whether there are differences in the extent of familial transmission for specific domains of cognitive function has not been systematically addressed. METHODS: We employed variance components analysis, as implemented in SOLAR-Eclipse, to evaluate the evidence of familial transmission for empirically derived composite scores representing attention, working memory, verbal learning, verbal retention, and memory for faces. We contrast estimates for adult- and childhood-onset schizophrenia families and matched community control pedigrees, and compare our findings to previous reports based on analogous neurocognitive assessments. RESULTS: We observed varying degrees of familial transmission; attention and working memory yielded comparable, significant estimates for adult-onset and community control pedigrees; verbal learning was significant for childhood-onset and community control pedigrees; and facial memory demonstrated significant familial transmission only for childhood-onset schizophrenia. Model-fitting analyses indicated significant differences in familiality between adult- and childhood-onset schizophrenia for attention, working memory, and verbal learning. CONCLUSIONS: By comprehensively assessing a wide range of neurocognitive domains in adult- and childhood-onset schizophrenia families, we provide additional support for specific neurocognitive domains as schizophrenia endophenotypes. Whereas comparable estimates of familial transmission for certain dimensions of cognitive functioning support a shared etiology of adult- and childhood-onset neurocognitive function, observed differences may be taken as preliminary evidence of partially divergent multifactorial architectures.

Comparing factor, class, and mixture models of cannabis initiation and DSM cannabis use disorder criteria, including craving, in the Brisbane longitudinal twin study.

Accumulating evidence suggests that the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying factor. However, it remains possible that models with additional factors, or latent class models or hybrid models, may better explain the data. Using structured interviews, 626 adult male and female twins provided complete data on symptoms of cannabis abuse and dependence, plus a craving criterion. We compared latent factor analysis, latent class analysis, and factor mixture modeling using normal theory marginal maximum likelihood for ordinal data. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-IV criteria and determine whether DSM-5 craving loads onto a general factor. When compared with latent class and mixture models, factor models provided a better fit to the data. When conditioned on initiation and cannabis use, the association between criteria for abuse, dependence, withdrawal, and craving were best explained by two correlated latent factors for males and females: a general risk factor to CUD and a factor capturing the symptoms of social and occupational impairment as a consequence of frequent use. Secondary analyses revealed a modest increase in the prevalence of DSM-5 CUD compared with DSM-IV cannabis abuse or dependence. It is concluded that, in addition to a general factor with loadings on cannabis use and symptoms of abuse, dependence, withdrawal, and craving, a second clinically relevant factor defined by features of social and occupational impairment was also found for frequent cannabis use.

Genetic and environmental influences of white and gray matter signal contrast: a new phenotype for imaging genetics?

The estimation of cortical thickness is in part dependent on the degree of contrast in T1 signal intensity between white matter and gray matter along the cortical mantle. The ratio of white matter to gray matter signal (WM/GM contrast) has been found to vary as a function of age and Alzheimer's disease status, suggesting a biological component to what might otherwise be labeled as a nuisance variable. The aim of the present study was to determine if measures of WM/GM contrast are genetically influenced, as well as the degree to which this phenotype may be related to the genetic and environment determinants of cortical thickness. Participants were 514 male twins (130 monozygotic, 97 dizygotic pairs, and 60 unpaired individuals) from the Vietnam Era Twin Study of Aging. Ages ranged from 51 to 59 years. Measures of WM/GM contrast and cortical thickness were derived for 66 cortical regions of interest (ROI) using FreeSurfer-based methods. Univariate and bivariate twin analyses were used in order to estimate the heritability of WM/GM contrast, as well as the degree of shared genetic and environmental variance between WM/GM contrast and cortical thickness. WM/GM contrast was found to be significantly heritable in the majority of ROIs. The average heritability across individual ROIs was highest in the occipital lobe (.50), and lowest in the cingulate cortex (.24). Significant phenotypic correlations between WM/GM contrast and cortical thickness were observed for most of the ROIs. The majority of the phenotypic correlations were negative, ranging from ?.11 to ?.54. Of the 66 associations, only 17 significant genetic correlations were found, ranging from ?.16 to ?.34, indicating small amounts of shared genetic variance. The majority of the phenotypic correlations were accounted for by small unique environmental effects common between WM/GM contrast and cortical thickness. These findings demonstrate that like cortical thickness, WM/GM contrast is a genetically influenced brain structure phenotype. The lack of significant genetic correlations with cortical thickness suggests that this measure potentially represents a unique source of genetic variance, one that has yet to be explored by the field of imaging genetics.

White matter heritability using diffusion tensor imaging in neonatal brains.

Understanding genetic and environmental effects on white matter development in the first years of life is of great interest, as it provides insights into the etiology of neurodevelopmental disorders. In this study, the genetic and environmental effects on white matter were estimated using data from 173 neonatal twin subjects. Diffusion tensor imaging scans were acquired around 40 days after birth and were non-rigidly registered to a group-specific atlas and parcellated into 98 ROIs. A model of additive genetic, and common and specific environmental variance components was used to estimate overall and regional genetic and environmental contributions to diffusion parameters of fractional anisotropy, radial diffusivity, and axial diffusivity. Correlations between the regional heritability values and diffusion parameters were also examined. Results indicate that individual differences in overall white matter microstructure, represented by the average diffusion parameters over the whole brain, are heritable, and estimates are higher than found in studies in adults. Estimates of genetic and environmental variance components vary considerably across different white matter regions. Significant positive correlations between radial diffusivity heritability and radial diffusivity values are consistent with regional genetic variation being modulated by maturation status in the neonatal brain: the more mature the region is, the less genetic variation it shows. Common environmental effects are present in a few regions that tend to be characterized by low radial diffusivity. Results from the joint diffusion parameter analysis suggest that multivariate modeling approaches might be promising to better estimate maturation status and its relationship with genetic and environmental effects.

Differential age and sex effects in the assessment of major depression: a population-based twin item analysis of the DSM criteria.

A twin item factor analytic model was developed to test for the presence of noninvariant age, sex, and age by sex interaction effects on the individual DSM-III-R criteria for major depression (MD). Based on 1-year reports, six of the nine MD criteria and duration requirement were found to have covariate factor loading and/or threshold effects that significantly deviated from their corresponding factor level expectations. A significant age effect was found for the binary duration variable factor loading. The 'loss of interest', 'weight problems' and 'psychomotor problems' criteria all displayed forms of threshold only effects. 'Depressed mood', 'fatigue', and 'feeling worthless' had more complex patterns that included both factor loading and threshold effects. A significant factor age by sex interaction effect indicating an increasing female mean difference with age was found to be largely associated with the presence of differential threshold covariate effects. Disagreement between estimated factor scores and DSM-derived affected vs. unaffected classification was approximately 1.3%. Status on the duration requirement was found to be the one feature common to all discrepancies. The MD criteria set provided maximum information for calibrating MD factor scores in the scale region where discrepancies occurred. The dimensional modeling results are discussed in the broader context of epidemiological research and clinical assessment of major depression.

Assessment of generalized anxiety disorder diagnostic criteria in the National Comorbidity Survey and Virginia Adult Twin Study of Psychiatric and Substance Use Disorders.

The authors investigated measurement properties of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, generalized anxiety disorder (GAD) criteria in the National Comorbidity Survey and the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders (VATSPSUD). The two studies used different widely used instruments. There were significant (p < .001) differences in measurement of GAD due to age, study, and age-study interaction on item thresholds and factor loadings of GAD, especially when different stem-probe structures of interviews were taken into account. Item thresholds were estimated to differ by as much as -.74 as a function of age and .40 as a function of study. Despite these differences, factor scores derived from symptom criteria strongly predicted categorical diagnostic outcomes based on symptom count. It is concluded that interview structure, especially the stem-probe format of structured interviews, and wording had significant effects on study findings; that future studies in psychiatric epidemiology should use common structured interviews as much as possible; and that factor scores can be used in conjunction with sum scores as cut points to retain the advantages of both dimensional and categorical classification.

Methodological issues in the assessment of substance use phenotypes.

The measurement of behavior is inherently problematic, and this is especially true of substance use and abuse phenotypes. The contingent nature of many assessments, such that symptoms of abuse and dependence cannot be obtained from those who have not initiated substance use, presents special difficulties. Furthermore, it is not clear whether individual differences in liability to use, abuse and dependence are best characterized as dimensions or classes or a combination of both. This article outlines research designs and methods suitable for quantifying liability to substance use. The value of data collected from relatives is emphasized in this context, as they permit identification of models normally compromised because data on, e.g., substance dependence symptoms, are systematically missing in those who have not initiated use of the substance in question.

Endorsement frequencies and factor structure of DSM-III-R and DSM-IV Generalized Anxiety Disorder symptoms in women: implications for future research, classification, clinical practice and comorbidity.

UNLABELLED: We investigated dimensions of liability to Generalized Anxiety Disorder (GAD) and whether evidence exists for distinct pathological versus normal clusters in the population. Structured interviews were administered to a general population sample of 2,163 female twins in a cross-sectional design. Endorsement rates were estimated using full information maximum likelihood factor analyses of the DSM-III-R and DSM-IV GAD symptoms, which provides appropriate treatment of the stem-probe structure of the clinical interview. Endorsement rates were highest for symptoms retained in DSM-IV. For both DSM-III-R and DSM-IV, a two-factor model fit the data better than a single-factor model. There was no evidence for non-normality in the liability to GAD. For DSM-III-R, autonomic symptoms loaded on a factor with panic disorder, while fatiguability, difficulty concentrating and hypervigilance loaded on a factor with major depression. For DSM-IV, all items loaded on one factor, and muscle tension also loaded on a second. Major depression, panic, phobias and alcohol dependence diagnoses also loaded on the first factor. CONCLUSIONS: Future research involving structured interviews should take into account the stem-and-probe format and focus on common factors rather than separate disorders; GAD is not a unidimensional construct and pathological anxiety may differ only quantitatively from normal anxiety.

The heritability of Cluster B personality disorders assessed both by personal interview and questionnaire.

Whereas the heritability of common personality traits has been firmly established, the results of the few published studies on personality disorders (PDs) are highly divergent, with some studies finding high heredity and others very low. A problem with assessing personality disorders by means of interview is errors connected with interviewer bias. A way to overcome the problem is to use self-report questionnaires in addition to interviews. This study used both interview and questionnaire for assessing DSM-IV Cluster B personality disorders: antisocial personality disorder (APD), borderline (BPD), narcissistic (NPD), and histrionic (HPD). We assessed close to 2,800 twins from the Norwegian Institute of Public Health Twin Panel using a self-report questionnaire and, a few years later, the Structured Interview for DSM-IV Personality (SIDP-IV). Items from the self-report questionnaire that best predicted the PDs captured by the interview were then selected. Measurement models combining questionnaire and interview information were applied and were fitted using Mx. Whereas the heritability of Cluster B PDs assessed by interview was around .30, and around .40-.50 when assessed by self-report questionnaire, the heritability of the convergent latent factor, including information from both interview and self-report questionnaire was .69 for APD, .67 for BPD, .71 for NPD, and .63 for HPD. As is usually found for personality, the effect of shared-in families (familial) environment was zero. In conclusion, when both interview and self-report questionnaire are taken into account, the heritability of Cluster B PD appears to be in the upper range of previous findings for mental disorders.

Measurement non-invariance of DSM-IV narcissistic personality disorder criteria across age and sex in a population-based sample of Norwegian twins.

We investigated measurement non-invariance of DSM-IV narcissistic personality disorder (NPD) criteria across age and sex in a population-based cohort sample of 2794 Norwegian twins. Age had a statistically significant effect on the factor mean for NPD. Sex had a statistically significant effect on the factor mean and variance. Controlling for these factor level effects, item-level analysis indicated that the criteria were functioning differently across age and sex. After correcting for measurement differences at the item level, the latent factor mean effect for age was no longer statistically significant. The mean difference for sex remained statistically significant after correcting for item threshold effects. The results indicate that DSM-IV NPD criteria perform differently in males and females and across age. Differences in diagnostic rates across groups may not be valid without correcting for measurement non-invariance.

Semi-Nonparametric Methods for Detecting Latent Non-normality: A Fusion of Latent Trait and Ordered Latent Class Modeling.

Ordered latent class analysis (OLCA) can be used to approximate unidimensional latent distributions. The main objective of this study is to evaluate the method of OLCA in detecting non-normality of an unobserved continuous variable (i.e., a common factor) used to explain the covariation between dichotomous item-level responses. Using simulation, we compared a model in which probabilities of class membership were estimated to a restricted submodel in which class memberships were fixed to normal Gauss-Hermite quadrature values. Our results indicate that the likelihood ratio statistic follows a predictable chi-square distribution for a wide range of sample sizes (N = 500-12,000) and test instrument characteristics, and has reasonable power to detect non-normality in cases of moderate effect sizes. Furthermore, under situations of large sample sizes, large numbers of items, or centrally located item difficulties, simulations suggest that it may be possible to describe the shape of latent trait distributions. Application to data on the symptoms of major depression, assessed in the National Comorbidity Survey, suggests that the latent trait does not depart from normality in men but does so to a small but significant extent in women.