Showing papers by "Michael C. Neale published in 2009"
TL;DR: It is demonstrated that cortical volume measures combine at least 2 distinct sources of genetic influences, and using volume in a genetically informative study, or as an endophenotype for a disorder, may confound the underlying genetic architecture of brain structure.
Abstract: Neuroimaging studies examining the effects of aging and neuropsychiatric disorders on the cerebral cortex have largely been based on measures of cortical volume. Given that cortical volume is a product of thickness and surface area, it is plausible that measures of volume capture at least 2 distinct sets of genetic influences. The present study aims to examine the genetic relationships between measures of cortical surface area and thickness. Participants were men in the Vietnam Era Twin Study of Aging (110 monozygotic pairs and 92 dizygotic pairs). Mean age was 55.8 years (range: 51-59). Bivariate twin analyses were utilized in order to estimate the heritability of cortical surface area and thickness, as well as their degree of genetic overlap. Total cortical surface area and average cortical thickness were both highly heritable (0.89 and 0.81, respectively) but were essentially unrelated genetically (genetic correlation = 0.08). This pattern was similar at the lobar and regional levels of analysis. These results demonstrate that cortical volume measures combine at least 2 distinct sources of genetic influences. We conclude that using volume in a genetically informative study, or as an endophenotype for a disorder, may confound the underlying genetic architecture of brain structure.
1,136 citations
TL;DR: The observation that regions associated with complex cognitive processes such as language, tool use, and executive function are more heritable in adolescents than children is consistent with previous studies showing that IQ becomes increasingly heritable with maturity.
Abstract: In this report, we present the first regional quantitative analysis of age-related differences in the heritability of cortical thickness using anatomic MRI with a large pediatric sample of twins, twin siblings, and singletons (n = 600, mean age 11.1 years, range 5-19). Regions of primary sensory and motor cortex, which develop earlier, both phylogenetically and ontologically, show relatively greater genetic effects earlier in childhood. Later developing regions within the dorsal prefrontal cortex and temporal lobes conversely show increasingly prominent genetic effects with maturation. The observation that regions associated with complex cognitive processes such as language, tool use, and executive function are more heritable in adolescents than children is consistent with previous studies showing that IQ becomes increasingly heritable with maturity(Plomin et al. 1997: Psychol Sci 8:442-447). These results suggest that both the specific cortical region and the age of the population should be taken into account when using cortical thickness as an intermediate phenotype to link genes, environment, and behavior.
310 citations
TL;DR: It is suggested that genetic variance has a dominant influence on total variance of factors associated with CVD and MetS and support the proposal of one or more underlying pathologies of MetS.
131 citations
TL;DR: The five anxiety disorders all share genetic and environmental risk factors, which has implications for the revision of the anxiety disorder section in DSM–V.
Abstract: Background
Twin data permit decomposition of comorbidity into genetically and environmentally derived correlations. No previous twin study includes all major forms of anxiety disorder.
Aims
To estimate the degree to which genetic and environmental risk factors are shared rather than unique to dimensionally scored panic disorder, generalised anxiety disorder, phobias, obsessive–compulsive disorder and post-traumatic stress disorder.
Method
Data obtained from 2801 young-adult Norwegian twins by means of the Composite International Diagnostic Interview were analysed with the Mx program.
Results
A multivariate common factor model fitted best. The latent liability to all anxiety disorders was substantially more heritable (54%) than the individual disorders (23% to 40%). Most of the genetic effect was common to the disorders. Genes contributed just over 50% to the covariance between liabilities.
Conclusions
The five anxiety disorders all share genetic and environmental risk factors. This has implications for the revision of the anxiety disorder section in DSM–V.
124 citations
TL;DR: An extension of previous extended twin family models, the Cascade model is introduced, which uses information on twins as well as their siblings, spouses, parents, and children to differentiate two genetic and six environmental sources of phenotypic variation.
Abstract: The classical twin design uses data on the variation of and covariation between monozygotic and dizygotic twins to infer underlying genetic and environmental causes of phenotypic variation in the population. By using data from additional relative classes, such as parents, extended twin family designs more comprehensively describe the causes of phenotypic variation. This article introduces an extension of previous extended twin family models, the Cascade model, which uses information on twins as well as their siblings, spouses, parents, and children to differentiate two genetic and six environmental sources of phenotypic variation. The Cascade also relaxes assumptions regarding mating and cultural transmission that existed in previous extended twin family designs. The estimation of additional parameters and relaxation of assumptions is potentially important, not only because it allows more fine-grained descriptions of the causes of phenotypic variation, but more importantly, because it can reduce the biases in parameter estimates that exist in earlier designs.
121 citations
TL;DR: The results suggested that the α5 and α3 subunits play a significant role in both nicotine dependence and alcohol abuse/dependence, however, the opposite effects with nicotine dependence, alcohol abuse or dependence were puzzling and future studies are necessary to resolve this issue.
Abstract: Nicotinic acetylcholine receptors bind to nicotine and initiate the physiological and pharmacological responses to tobacco smoking. In this report, we studied the association of α5 and α3 subunits with nicotine dependence and with the symptoms of alcohol and cannabis abuse and dependence in two independent epidemiological samples (n = 815 and 1,121, respectively). In this study, seven single nucleotide polymorphisms were genotyped in the CHRNA5 and CHRNA3 genes. In both samples, we found that the same alleles of rs16969968 (P = 0.0068 and 0.0028) and rs1051730 (P = 0.0237 and 0.0039) were significantly associated with the scores of Fagerstrom test for nicotine dependence (FTND). In the analyses of the symptoms of abuse/dependence of alcohol and cannabis, we found that rs16969968 and rs1051730 were significantly associated with the symptoms of alcohol abuse or dependence (P = 0.0072 and 0.0057) in the combined sample, but the associated alleles were the opposite of that of FTND. No association with cannabis abuse/dependence was found. These results suggested that the α5 and α3 subunits play a significant role in both nicotine dependence and alcohol abuse/dependence. However, the opposite effects with nicotine dependence and alcohol abuse/dependence were puzzling and future studies are necessary to resolve this issue. © 2009 Wiley-Liss, Inc.
103 citations
TL;DR: The results show that the latent shared environmental factors in cannabis initiation and abuse can be explained by measured aspects of the shared environment--those responsible for variation in cannabis availability.
Abstract: Aims
Although previous twin studies have modelled the association between drug initiation and abuse, none has included the obvious risk factor of drug availability. Our aim is to determine whether the genetic and environmental risk factors for cannabis availability also generate variation in cannabis initiation and/or progression to DSM-IV symptoms of abuse.
102 citations
TL;DR: This editorial outlines the development of genome-wide association studies in psychiatry and highlights the opportunities for advancing understanding of the biological underpinnings and nosological structure of psychiatric disorders.
Abstract: Over the past 2 years genome-wide association studies have made major contributions to understanding the genetic architecture of many common human diseases. This editorial outlines the development of such studies in psychiatry and highlights the opportunities for advancing understanding of the biological underpinnings and nosological structure of psychiatric disorders.
68 citations
TL;DR: A novel method that combines classical quantitative genetic methodologies for variance decomposition with recently developed semi-multivariate algorithms for high-resolution measurement of phenotypic covariance is described, suggesting that genetics plays a large role in global brain patterning of cortical thickness in this manner.
58 citations
TL;DR: The results suggest the DSM-IV BPD ‘impulsivity’ and ‘affective instability’ criteria function differentially with respect to age and sex, with impulsivity being especially problematic.
Abstract: Background Despite its importance as a paradigmatic personality disorder, little is known about the measurement invariance of the DSM-IV borderline personality disorder (BPD) criteria; that is, whether the criteria assess the disorder equivalently across different groups. Method BPD criteria were evaluated at interview in 2794 young adult Norwegian twins. Analyses, based on item-response modeling, were conducted to test for differential age and sex moderation of the individual BPD criteria characteristics given factor-level covariate effects. Results Confirmatory factor analytic results supported a unidimensional structure for the nine BPD criteria. Compared to males, females had a higher BPD factor mean, larger factor variance and there was a significant age by sex interaction on the factor mean. Strong differential sex and age by sex interaction effects were found for the 'impulsivity' criterion factor loading and threshold. Impulsivity related to the BPD factor poorly in young females but improved significantly in older females. Males reported more impulsivity compared to females and this difference increased with age. The 'affective instability' threshold was also moderated, with males reporting less than expected. Conclusions The results suggest the DSM-IV BPD 'impulsivity' and 'affective instability' criteria function differentially with respect to age and sex, with impulsivity being especially problematic. If verified, these findings have important implications for the interpretation of prior research with these criteria. These non-invariant age and sex effects may be identifying criteria-level expression features relevant to BPD nosology and etiology. Criterion functioning assessed using modern psychometric methods should be considered in the development of DSM-V.
53 citations
TL;DR: PGD was assumed to be an environmental, upstream risk factor for CU, but data are not consistent with this hypothesis and suggest that the liability to affiliate with deviant peers is explained more clearly by a combination of genetic and environmental factors that are indexed by CU.
Abstract: Background
Peer group deviance (PGD) is strongly linked to liability to drug use including cannabis. Our aim was to model the genetic and environmental association, including direction of causation, between PGD and cannabis use (CU).
TL;DR: AN symptoms are differentially heritable, and specific criteria such as those related to body weight and weight loss history represent more biologically driven potential endophenotypes or liability indices.
Abstract: BackgroundAssessment of eating disorders at the symptom level can facilitate the refinement of phenotypes. We examined genetic and environmental contributions to liability to anorexia nervosa (AN) symptoms in a population-based twin sample using a genetic common pathway model.MethodParticipants were from the Norwegian Institute of Public Health Twin Panel (NIPHTP) and included all female monozygotic (MZ; 448 complete pairs and four singletons) and dizygotic (DZ; 263 complete pairs and four singletons) twins who completed the Composite International Diagnostic Interview (CIDI) assessing DSM-IV Axis I and ICD-10 criteria. Responses to items assessing AN symptoms were included in a model fitted using the marginal maximum likelihood (MML) approach.ResultsHeritability of the overall AN diagnosis was moderate [a2=0.22, 95% confidence interval (CI) 0.0–0.50] whereas heritabilities of the specific items varied. Heritability estimates for weight loss items were moderate (a2=0.31–0.34) and items assessing weight concern when at a low weight were smaller (0.18–0.29). Additive genetic factors contributed little to the variance of amenorrhea, which was most strongly influenced by unshared environment (a2=0.16, e2=0.71).ConclusionsAN symptoms are differentially heritable. Specific criteria such as those related to body weight and weight loss history represent more biologically driven potential endophenotypes or liability indices. The results regarding weight concern differ somewhat from those of previous studies, highlighting the importance of assessing genetic and environmental influences on variance of traits within specific subgroups of interest.
TL;DR: Simulation results indicate that analyses of ordinal and binary data can recover both the raw and standardized patterns of results, and it is demonstrated that when using binary data, constraining the total variance to unity for a given value of the moderator is sufficient to ensure identification.
Abstract: Following the publication of Purcell’s approach to the modeling of gene by environment interaction in 2002, the interest in G × E modeling in twin and family data increased dramatically. The analytic techniques described by Purcell were designed for use with continuous data. Here we explore the re-parameterization of these models for use with ordinal and binary outcome data. Analysis of binary and ordinal data within the context of a liability threshold model traditionally requires constraining the total variance to unity to ensure identification. Here, we demonstrate an alternative approach for use with ordinal data, in which the values of the first two thresholds are fixed, thus allowing the total variance to change as function of the moderator. We also demonstrate that when using binary data, constraining the total variance to unity for a given value of the moderator is sufficient to ensure identification. Simulation results indicate that analyses of ordinal and binary data can recover both the raw and standardized patterns of results. However, the scale of the results is dependent on the specification of (threshold or variance) constraints rather than the underlying distribution of liability. Example Mx scripts are provided.
01 Jan 2009
TL;DR: The research designs and statistical methods that are in popular use in behavioral genetics (BG) are described, to provide a general and extensible infrastructure for the modeling of genetically informative data.
Abstract: The main goal of this chapter is to describe the research designs and statistical methods that are in popular use in behavioral genetics (BG). We begin with a brief overview of the historical background to BG in general and twin studies in particular. Next, we describe some elementary statistics required for understanding biometrical modeling. Then follows a statistical model for genetic variation, as articulated by Fisher in his classic 1918 paper, in which additive and dominance genetic variance terms are defined. The coefficients of resemblance between relatives derived from this model are then implemented in structural equation models for the analysis of data from twins and other relatives. Overall the intent is to provide a general and extensible infrastructure for the modeling of genetically informative data.
TL;DR: Although the contribution of maternal and fetal genetic factors was supported using both outcomes, additional births and/or extended relationships are required to precisely estimate both genetic effects simultaneously.
Abstract: The analysis of genetic and environmental contributions to preterm birth is not straightforward in family studies, as etiology could involve both maternal and fetal genes. Markov Chain Monte Carlo (MCMC) methods are presented as a flexible approach for defining user-specified covariance structures to handle multiple random effects and hierarchical dependencies inherent in children of twin (COT) studies of pregnancy outcomes. The proposed method is easily modified to allow for the study of gestational age as a continuous trait and as a binary outcome reflecting the presence or absence of preterm birth. Estimation of fetal and maternal genetic factors and the effect of the environment are demonstrated using MCMC methods implemented in WinBUGS and maximum likelihood methods in a Virginia COT sample comprising 7,061 births. In summary, although the contribution of maternal and fetal genetic factors was supported using both outcomes, additional births and/or extended relationships are required to precisely estimate both genetic effects simultaneously. We anticipate the flexibility of MCMC methods to handle increasingly complex models to be of particular relevance for the study of birth outcomes.
TL;DR: It is suggested that in studies such as that of Hong et al based only on first-degree relatives, it would be advisable to use a more generic term such as transmissibility or familiality rather than the more specific term heritability.
Abstract: In their recent article, Hong et al1 reported heritabilities of auditory sensory gating. As they defined it in their article, heritability reflects the proportion of overall variability in a trait in a population that results from additive genetic effects. Within human populations, such estimates have traditionally relied on special relationships that can (with some well-understood limitations) disentangle genetic from familial-environmental effects. The most popular of these methods have been twin studies comparing monozygotic and dizygotic twin pairs and various adoption designs.
However, in their study, Hong et al do not use these standard approaches. Rather, they examine individuals with schizophrenia (n=102) and 74 of their first-degree relatives. Heritabilities are estimated from sibling-sibling and parent-offspring pairs using the program SOLAR.2 The problem with this approach is that data from these 2 relationships alone do not contain information that can, with any confidence, disentangle genetic from familial-environmental sources of resemblance. This is because for the major source of genetic resemblance—additive genetic effects—the expected correlation is the same in both of these relationships: +0.50. It is true that nonadditive genetic effects contribute to sib-sib but not to parent-offspring resemblance. However, given that there may be considerable sharing of environmental factors for both of these relationships, the a priori assumption that their effects are absent is hard to justify for many phenotypes.
We do not herein claim that heritability estimates from twin or adoption studies are without concerns. But they are based on well-understood quantitative genetic principles and their limitations have been widely examined (see Kendler and Prescott3 for concerns about the twin method). In studies such as that of Hong et al based only on first-degree relatives, we suggest that it would be advisable to use a more generic term such as transmissibility or familiality rather than the more specific term heritability.
TL;DR: Results indicate that biases in the estimation of variance components depend both on the types of relative available for analysis, and on the underlying genetic and environmental architecture of the phenotype of interest.
Abstract: The extended twin kinship design allows the simultaneous testing of additive and nonadditive genetic, shared and individual-specific environmental factors, as well as sex differences in the expression of genes and environment in the presence of assortative mating and combined genetic and cultural transmission (Eaves et al., 1999). It also handles the contribution of these sources of variance to the (co)variation of multiple phenotypes. Keller et al. (2008) extended this comprehensive model for family resemblance to allow or a flexible specification of assortment and vertical transmission. As such, it provides a general framework which can easily be reduced to fit subsets of data such as twin-parent data, children-of-twins data, etc. A flexible Mx specification of this model that allows handling of these various designs is presented in detail and applied to data from the Virginia 30,000. Data on height, body mass index, smoking status, church attendance, and political affiliation were obtained from twins and their families. Results indicate that biases in the estimation of variance components depend both on the types of relative available for analysis, and on the underlying genetic and environmental architecture of the phenotype of interest.
TL;DR: Findings suggest that common variation in the GABRA2, G ABRA3, GABra6, and GABRG2 genes does not play a major role in liability to anxiety spectrum disorders.
Abstract: Background: Human anxiety disorders are complex diseases with relatively unknown etiology. Dysfunction of the Gamma-aminobutyric acid (GABA) system has been implicated in many neuropsychiatric conditions, including anxiety and depressive disorders. In this investigation, we explored four GABA receptor genes for their possible associations with genetic risk for anxiety disorders and depression.Methods: Our study sample consisted of 589 cases and 539 controls selected from a large population-based twin registry based upon a latent genetic risk factor shared by several anxiety disorders, major depression, and neuroticism. We subjected these to a two-stage protocol, in which all candidate genetic markers were screened for association in stage 1 (N=376), the positive results of which were tested for replication in stage 2 (N=752). We analyzed data from 26 single nucleotide polymorphisms (SNPs) from four GABA receptor genes: GABRA2, GABRA3, GABRA6, and GABRG2. Results: Of the 26 SNPs genotyped in stage 1, we identified two markers in GABRA3 that met the threshold (P≤.1) to be tested in stage 2. Phenotypic associations of these two markers failed to replicate in stage 2. Conclusions: These findings suggest that common variation in the GABRA2, GABRA3, GABRA6, and GABRG2 genes does not play a major role in liability to anxiety spectrum disorders. Depression and Anxiety 26:998–1003, 2009. Published 2009 Wiley-Liss, Inc.
TL;DR: Both samples showed an association between Epac‐1 gene variants and anxiety and depression, but for different variants or in opposite directions, and divergent results could be due to differences in linkage disequilibrium between the investigated SNPs and a functional polymorphism in the Dutch and USA sample.
Abstract: Deficiency in signal transduction might play a role in the development of anxiety and depression, as suggested by a study on the involvement of the PKA-independent Epac pathway. We investigated the association between Epac-1 gene variants, also known as RapGEF-3, and measures of anxiety and depression in a Dutch twin-family sample. Replication was sought in a USA sample consisting of unrelated individuals. Genotype and phenotype data were available for 910 Dutch and 684 USA individuals. Longitudinal self-report measures of neuroticism, anxiety and depression and genetic factor scores (GFS-NL), based on these measures, were analyzed in the Dutch sample. In the USA sample, neuroticism and Genetic Factor Scores (GFS-USA), based on neuroticism and diagnoses of anxiety disorders and depression, were analyzed. Three intronic SNPs were genotyped. Analyses were performed in QTDT. Genotype and haplotype frequencies differed significantly between the samples. In the Dutch sample, rs2072115 showed a significant dominant effect for anxiety and depression. Subjects with haplotype G-C-C (ordered rs2072115-rs757281-2074533) had significantly lower anxiety, neuroticism and GFS-NL scores. In the USA sample, a significant additive effect of rs2074533 on GFS-USA was found. Subjects with haplotypes G-C-C and A-C-T had significantly higher and lower GFS-USA scores, respectively. Both samples showed an association between Epac-1 gene variants and anxiety and depression, but for different variants or in opposite directions. The divergent results could be due to differences in linkage disequilibrium between the investigated SNPs and a functional polymorphism in the Dutch and USA sample.
TL;DR: The data suggests that common variations in the CREB1 gene do not appear to increase susceptibility for MDD or related phenotypes.
Abstract: Cyclic AMP response element binding protein (CREB) has been implicated in behavioral models of anxiety and depression, antidepressant response in humans, and suicide One group reported a female-specific association of the CREB1 gene in early-onset Major Depressive Disorder (MDD), while another found no evidence of association with this phenotype In this study, we sought to examine the evidence for association of the CREB1 gene to MDD and related phenotypes We used multivariate structural equation modeling to identify and select twin pairs that scored at the extremes of a latent genetic risk factor shared by MDD, neuroticism, and several anxiety disorders from the Virginia Twin Registry Using one member from each of these pairs, the resulting sample of 589 cases (including 473 subjects with lifetime MDD) and 539 controls were entered into a 2-stage association study in which genetic markers were screened in stage 1, the positive results of which were tested for replication in stage 2 Eight SNP markers selected to capture the major allelic variation across the haplotype block containing CREB1 were analyzed for differences between cases and controls Several markers showed criterion differences between cases and controls in the stage 1 sample with some evidence of sex specific effects However, none of these markers were significant in stage 2 in either sex individually or combined Our data suggests that common variations in the CREB1 gene do not appear to increase susceptibility for MDD or related phenotypes
TL;DR: A computational framework suitable for a data-driven approach to structural equation modeling (SEM) is presented and several workflows for modeling functional magnetic resonance imaging (fMRI) data within this framework are described.
Abstract: We present a computational framework suitable for a data-driven approach to structural equation modeling (SEM) and describe several workflows for modeling functional magnetic resonance imaging (fMRI) data within this framework. The Computational Neuroscience Applications Research Infrastructure (CNARI) employs a high-level scripting language called Swift, which is capable of spawning hundreds of thousands of simultaneous R processes (R Core Development Team, 2008), consisting of self-contained structural equation models, on a high performance computing system (HPC). These self-contained R processing jobs are data objects generated by OpenMx, a plug-in for R, which can generate a single model object containing the matrices and algebraic information necessary to estimate parameters of the model. With such an infrastructure in place a structural modeler may begin to investigate exhaustive searches of the model space. Specific applications of the infrastructure, statistics related to model fit, and limitations are discussed in relation to exhaustive SEM. In particular, we discuss how workflow management techniques can help to solve large computational problems in neuroimaging.
TL;DR: A new method of efficient permutation is reported, which greatly reduces the number of permutation tests required for genome-wide scanning, making it suitable for use in multivariate and other computationally intensive linkage analyses.
Abstract: Linkage analysis in multivariate or longitudinal context presents both statistical and computational challenges. The permutation test can be used to avoid some of the statistical challenges, but it substantially adds to the computational burden. Utilizing the distributional dependencies between p (defined as the proportion of alleles at a locus that are identical by descent (IBD) for a pairs of relatives, at a given locus) and the permutation test we report a new method of efficient permutation. In summary, the distribution of p for a sample of relatives at locus x is estimated as a weighted mixture of p drawn from a pool of 'representative' p distributions observed at other loci. This weighting scheme is then used to sample from the distribution of the permutation tests at the representative loci to obtain an empirical P-value at locus x (which is asymptotically distributed as the permutation test at loci x). This weighted mixture approach greatly reduces the number of permutation tests required for genome-wide scanning, making it suitable for use in multivariate and other computationally intensive linkage analyses. In addition, because the distribution of p is a property of the genotypic data for a given sample and is independent of the phenotypic data, the weighting scheme can be applied to any phenotype (or combination of phenotypes) collected from that sample. We demonstrate the validity of this approach through simulation.