Using the tools of genetic epidemiology to understand sex differences in neuropsychiatric disorders.

Many neuropsychiatric disorders exhibit differences in prevalence, age of onset, symptoms or course of illness between males and females. For the most part, the origins of these differences are not well understood. In this article, we provide an overview of sex differences in psychiatric disorders including autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD), anxiety, depression, alcohol and substance abuse, schizophrenia, eating disorders and risk of suicide. We discuss both genetic and nongenetic mechanisms that have been hypothesized to underlie these differences, including ascertainment bias, environmental stressors, X- or Y-linked risk loci, and differential liability thresholds in males and females. We then review the use of twin, family and genome-wide association approaches to study potential genetic mechanisms of sex differences and the extent to which these designs have been employed in studies of psychiatric disorders. We describe the utility of genetic epidemiologic study designs, including classical twin and family studies, large-scale studies of population registries, derived recurrence risks, and molecular genetic analyses of genome-wide variation that may enhance our understanding sex differences in neuropsychiatric disorders.

Adolescent cannabis use, cognition, brain health and educational outcomes: A review of the evidence.

We review the findings of systematic reviews and meta-analyses of case-control studies that examine brain functioning and cognitive correlates of adolescent cannabis use using structural and functional neuroimaging tools and standardised neuropsychological tests. We also examine prospective epidemiological studies on the possible effects of adolescent and young adult cannabis use on cognitive performance in adult life and the completion of secondary education. We summarize the findings of studies in each of these areas that have been published since the most recent systematic review. Systematic reviews find that adolescent cannabis use is inconsistently associated with alterations in the structure of prefrontal and temporal brain regions. Meta-analyses reveal functional alterations in the parietal cortex and putamen. Differences in the orbitofrontal cortex predate cannabis use; it is unclear if they are affected by continued cannabis use and prolonged abstinence. Longitudinal and twin studies report larger declines in IQ among cannabis users than their non-using peers but it is unclear whether these findings can be attributed to cannabis use or to genetic, mental health and environmental factors. Several longitudinal studies and a meta-analysis of cross-sectional studies suggest that there is some cognitive recovery after abstinence from cannabis. Longitudinal studies and some twin studies have found that cannabis users are less likely to complete secondary school than their non-using controls. This association might reflect an effect of cannabis use and/or the social environment of cannabis users and their cannabis using peers. Cognitive performance is altered in some domains (e.g. IQ, verbal learning) in young people while they are regularly using cannabis. There are two important messages to adolescents and young adults: First, cannabis has potentially detrimental effects on cognition, brain and educational outcomes that persist beyond acute intoxication. Second, impaired cognitive function in cannabis users appears to improve with sustained abstinence.

FinnTwin16: A Longitudinal Study from Age 16 of a Population-Based Finnish Twin Cohort.

The purpose of this review is to provide a detailed and updated description of the FinnTwin16 (FT16) study and its future directions. The Finnish Twin Cohort comprises three different cohorts: the Older Twin Cohort established in the 1970s and the FinnTwin12 and FT16 initiated in the 1990s. FT16 was initiated in 1991 to identify the genetic and environmental precursors of alcoholism, but later the scope of the project expanded to studying the determinants of various health-related behaviors and diseases in different stages of life. The main areas addressed are alcohol use and its consequences, smoking, physical activity, overall physical health, eating behaviors and eating disorders, weight development, obesity, life satisfaction and personality. To date, five waves of data collection have been completed and the sixth is now planned. Data from the FT16 cohort have contributed to several hundred studies and many substudies, with more detailed phenotyping and collection of omics data completed or underway. FT16 has also contributed to many national and international collaborations.

Genetic Approaches to Bronchopulmonary Dysplasia.

Bronchopulmonary dysplasia (BPD) remains a common and challenging complication of prematurity, with limited effective strategies at the neonatologist's disposal. Throughout the years, our understanding of this complex syndrome has broadened. Instead of solely attributing this disease to the effects of prematurity and injuries to the lung from mechanical ventilation, it is now accepted to be a multifactorial disease. Recent research efforts have focused on investigating the gene-environment interactions that may influence an infant's susceptibility toward the development of BPD. So far, success has been limited but promising, offering hope that in the future, novel therapies will be available to ameliorate the risk for BPD.

Prediction of drug response and adverse drug reactions: From twin studies to Next Generation Sequencing.

Understanding and predicting inter-individual differences related to the success of drug therapy is of tremendous importance, both during drug development and for clinical applications. Importantly, while seminal twin studies indicate that the majority of inter-individual differences in drug disposition are driven by hereditary factors, common genetic polymorphisms explain only less than half of this genetically encoded variability. Recent progress in Next Generation Sequencing (NGS) technologies has for the first time allowed to comprehensively map the genetic landscape of human pharmacogenes. Importantly, these projects have unveiled vast numbers of rare genetic variants, which are estimated to contribute substantially to the missing heritability of drug metabolism phenotypes. However, functional interpretation of these rare variants remains challenging and constitutes one of the important frontiers of contemporary pharmacogenomics. Furthermore, NGS technologies face challenges in the interrogation of genes residing in complex genomic regions, such as CYP2D6 and HLA genes. We here provide an update of the implementation of pharmacogenomic variations in the clinical setting and present emerging strategies that facilitate the translation of NGS data into clinically useful information. Importantly, we anticipate that these developments will soon result in a paradigm shift of pre-emptive genotyping away from the interrogation to candidate variants and towards the comprehensive profiling of an individuals genotype, thus allowing for a true individualization of patient drug treatment regimens.

Type I Error Rates and Parameter Bias in Multivariate Behavioral Genetic Models.

For many multivariate twin models, the numerical Type I error rates are lower than theoretically expected rates using a likelihood ratio test (LRT), which implies that the significance threshold for statistical hypothesis tests is more conservative than most twin researchers realize. This makes the numerical Type II error rates higher than theoretically expected. Furthermore, the discrepancy between the observed and expected error rates increases as more variables are included in the analysis and can have profound implications for hypothesis testing and statistical inference. In two simulation studies, we examine the Type I error rates for the Cholesky decomposition and Correlated Factors models. Both show markedly lower than nominal Type I error rates under the null hypothesis, a discrepancy that increases with the number of variables in the model. In addition, we observe slightly biased parameter estimates for the Cholesky decomposition and Correlated Factors models. By contrast, if the variance-covariance matrices for variance components are estimated directly (without constraints), the numerical Type I error rates are consistent with theoretical expectations and there is no bias in the parameter estimates regardless of the number of variables analyzed. We call this the direct symmetric approach. It appears that each model-implied boundary, whether explicit or implicit, increases the discrepancy between the numerical and theoretical Type I error rates by truncating the sampling distributions of the variance components and inducing bias in the parameters. The direct symmetric approach has several advantages over other multivariate twin models as it corrects the Type I error rate and parameter bias issues, is easy to implement in current software, and has fewer optimization problems. Implications for past and future research, and potential limitations associated with direct estimation of genetic and environmental covariance matrices are discussed.

Extending Causality Tests with Genetic Instruments: An Integration of Mendelian Randomization with the Classical Twin Design.

Although experimental studies are regarded as the method of choice for determining causal influences, these are not always practical or ethical to answer vital questions in health and social research (e.g., one cannot assign individuals to a "childhood trauma condition" in studying the causal effects of childhood trauma on depression). Key to solving such questions are observational studies. Mendelian Randomization (MR) is an influential method to establish causality in observational studies. MR uses genetic variants to test causal relationships between exposures/risk factors and outcomes such as physical or mental health. Yet, individual genetic variants have small effects, and so, when used as instrumental variables, render MR liable to weak instrument bias. Polygenic scores have the advantage of larger effects, but may be characterized by horizontal pleiotropy, which violates a central assumption of MR. We developed the MR-DoC twin model by integrating MR with the Direction of Causation twin model. This model allows us to test pleiotropy directly. We considered the issue of parameter identification, and given identification, we conducted extensive power calculations. MR-DoC allows one to test causal hypotheses and to obtain unbiased estimates of the causal effect given pleiotropic instruments, while controlling for genetic and environmental influences common to the outcome and exposure. Furthermore, the approach allows one to employ strong instrumental variables in the form of polygenic scores, guarding against weak instrument bias, and increasing the power to detect causal effects of exposures on potential outcomes. Beside allowing to test pleiotropy directly, incorporating in MR data collected from relatives provide additional within-family data that resolve additional assumptions like random mating, the absence of the gene-environment interaction/covariance, no dyadic effects. Our approach will enhance and extend MR's range of applications, and increase the value of the large cohorts collected at twin/family registries as they correctly detect causation and estimate effect sizes even in the presence of pleiotropy.

Are your covariates under control? How normalization can re-introduce covariate effects.

Many statistical tests rely on the assumption that the residuals of a model are normally distributed. Rank-based inverse normal transformation (INT) of the dependent variable is one of the most popular approaches to satisfy the normality assumption. When covariates are included in the analysis, a common approach is to first adjust for the covariates and then normalize the residuals. This study investigated the effect of regressing covariates against the dependent variable and then applying rank-based INT to the residuals. The correlation between the dependent variable and covariates at each stage of processing was assessed. An alternative approach was tested in which rank-based INT was applied to the dependent variable before regressing covariates. Analyses based on both simulated and real data examples demonstrated that applying rank-based INT to the dependent variable residuals after regressing out covariates re-introduces a linear correlation between the dependent variable and covariates, increasing type-I errors and reducing power. On the other hand, when rank-based INT was applied prior to controlling for covariate effects, residuals were normally distributed and linearly uncorrelated with covariates. This latter approach is therefore recommended in situations were normality of the dependent variable is required.

El Registro de Gemelos de Murcia. Un recurso para la investigación sobre conductas relacionadas con la salud / The Murcia Twin Registry. A resource for research on health-related behaviour

Los diseños genéticamente informativos, y en particular los estudios de gemelos, constituyen la metodología más utilizada para analizar la contribución relativa de los factores genéticos y ambientales a la variabilidad interindividual. Básicamente, consisten en comparar el grado de similitud, con respecto a una característica o rasgo determinado, entre gemelos monocigóticos y dicigóticos. Además de la clásica estimación de heredabilidad, este tipo de registros permite una amplia variedad de análisis únicos por las características de la muestra. El Registro de Gemelos de Murcia es un registro de base poblacional centrado en el análisis de conductas relacionadas con la salud. Las prevalencias de problemas de salud observadas son comparables a las de otras muestras de referencia de ámbito regional y estatal, lo que avala su representatividad. En conjunto, sus características facilitan el desarrollo de diversas modalidades de investigación, además de diseños genéticamente informativos y la colaboración con distintas iniciativas y consorcios (AU)

Genetically informative designs and, in particular, twin studies, are the most widely used methodology to analyse the relative contribution of genetic and environmental factors to inter-individual variability. These studies basically compare the degree of phenotypical similarity between monozygotic and dizygotic twin pairs. In addition to the traditional estimate of heritability, this kind of registry enables a wide variety of analyses which are unique due to the characteristics of the sample. The Murcia Twin Registry is population-based and focused on the analysis of health-related behaviour. The observed prevalence of health problems is comparable to that of other regional and national reference samples, which guarantees its representativeness. Overall, the characteristics of the Registry facilitate developing various types of research as well as genetically informative designs, and collaboration with different initiatives and consortia (AU)

Sum Scores in Twin Growth Curve Models: Practicality Versus Bias.

To study behavioral or psychiatric phenotypes, multiple indices of the behavior or disorder are often collected that are thought to best reflect the phenotype. Combining these items into a single score (e.g. a sum score) is a simple and practical approach for modeling such data, but this simplicity can come at a cost in longitudinal studies, where the relevance of individual items often changes as a function of age. Such changes violate the assumptions of longitudinal measurement invariance (MI), and this violation has the potential to obfuscate the interpretation of the results of latent growth models fit to sum scores. The objectives of this study are (1) to investigate the extent to which violations of longitudinal MI lead to bias in parameter estimates of the average growth curve trajectory, and (2) whether absence of MI affects estimates of the heritability of these growth curve parameters. To this end, we analytically derive the bias in the estimated means and variances of the latent growth factors fit to sum scores when the assumption of longitudinal MI is violated. This bias is further quantified via Monte Carlo simulation, and is illustrated in an empirical analysis of aggression in children aged 3-12 years. These analyses show that measurement non-invariance across age can indeed bias growth curve mean and variance estimates, and our quantification of this bias permits researchers to weigh the costs of using a simple sum score in longitudinal studies. Simulation results indicate that the genetic variance decomposition of growth factors is, however, not biased due to measurement non-invariance across age, provided the phenotype is measurement invariant across birth-order and zygosity in twins.

Higher Rates of DZ Twinning in a Twenty-First Century Birth Cohort.

The Colorado Twin Registry is a population based registry initiated in 1984 with the involvement of the Colorado Department of Health, Division of Vital Statistics. Recruitment includes birth cohorts several years prior to 1984 and all subsequent years. As part of a recent evaluation of Colorado birth records for the years 2006 through 2008 we became aware of a shifting trend in the proportion of MZ and DZ twins in the Colorado population. Historically (Bulmer 1970 The biology of twinning in man, Clarendon, Oxford) we have expected a 1/3, 1/3, 1/3 ratio of MZ, same-sex DZ and opposite sex DZ twins in Caucasian populations. An excess of MZ pairs in most studies was assumed to be due to selection bias. Somewhat more recently, Hur et al.(1995 Behav Genet 25, 337-340) provided evidence that the DZ twinning rate was falling and that therefore selection bias was not the reason for higher MZ enrollment in most twin studies. They suggested that twin researchers might consider strategies to over-enroll DZ pairs to maximize statistical power. In contrast, we now find that of the 3217 twin births in Colorado from 2006 to 2008 with identified sex information the MZ rate is estimated at only 22%, and we have corroborating reports from other states of similar estimates. These were calculated applying Weinberg's rule which assumes an equal birth rate for same sex and opposite sex DZ pairs so that the proportion of MZ in a sample is the proportion of same sex (MM + FF) minus the proportion of opposite-sex (MF, FM). We explore factors, such as an increase in the proportion of non-Caucasian parents and an increase in average maternal age, which may contribute to this shift.

A meta-analysis of reflux genome-wide association studies in 6750 Northern Europeans from the general population.

BACKGROUND: Gastroesophageal reflux disease (GERD), the regurgitation of gastric acids often accompanied by heartburn, affects up to 20% of the general population. Genetic predisposition is suspected from twin and family studies but gene-hunting efforts have so far been scarce and no conclusive genome-wide study has been reported. We exploited data available from general population samples, and studied self-reported reflux symptoms in relation to genome-wide single nucleotide polymorphism (SNP) genotypes. METHODS: We performed a GWAS meta-analysis of three independent population-based cohorts from Sweden, Finland, and UK. GERD cases (n=2247) and asymptomatic controls (n=4503) were identified using questionnaire-derived symptom data. Upon stringent quality controls, genotype data for more than 2.5M markers were used for association testing. Bioinformatic characterization of genomic regions associated with GERD included gene-set enrichment analysis (GSEA), in silico prediction of genetic risk effects on gene expression, and computational analysis of drug-induced gene expression signatures using Connectivity Map (cMap). KEY RESULTS: We identified 30 GERD suggestive risk loci (P≤5×10-5 ), with concordant risk effects in all cohorts, and predicted functional effects on gene expression in relevant tissues. GSEA revealed involvement of GERD risk genes in biological processes associated with the regulation of ion channel and cell adhesion. From cMap analysis, omeprazole had significant effects on GERD risk gene expression, while antituberculosis and anti-inflammatory drugs scored highest among the repurposed compounds. CONCLUSIONS: We report a large-scale genetic study of GERD, and highlight genes and pathways that contribute to further our understanding of its pathogenesis and therapeutic opportunities.

Education and alcohol use: A study of gene-environment interaction in young adulthood.

The consequences of heavy alcohol use remain a serious public health problem. Consistent evidence has demonstrated that both genetic and social influences contribute to alcohol use. Research on gene-environment interaction (GxE) has also demonstrated that these social and genetic influences do not act independently. Instead, certain environmental contexts may limit or exacerbate an underlying genetic predisposition. However, much of the work on GxE and alcohol use has focused on adolescence and less is known about the important environmental contexts in young adulthood. Using data from the young adult wave of the Finnish Twin Study, FinnTwin12 (N = 3402), we used biometric twin modeling to test whether education moderated genetic risk for alcohol use as assessed by drinking frequency and intoxication frequency. Education is important because it offers greater access to personal resources and helps determine one's position in the broader stratification system. Results from the twin models show that education did not moderate genetic variance components and that genetic risk was constant across levels of education. Instead, education moderated environmental variance so that under conditions of low education, environmental influences explained more of the variation in alcohol use outcomes. The implications and limitations of these results are discussed.

El tipo de parto como variable predictora del desarrollo psicológico y la inteligencia en gemelos / The type of birth as predictor of psychological development and intelligence in twins

Introducción: En los últimos años se ha producido un aumento de las gestaciones múltiples en nuestro entorno. Dada la elevada tasa de prematuridad y complicaciones perinatales que conllevan, constituyen un grupo de especial vulnerabilidad no sólo en el periodo perinatal, sino a largo plazo. Objetivos: Analizar la influencia del tipo de parto y otras variables perinatales, como el orden de nacimiento, en el desarrollo a largo plazo de niños nacidos en un parto gemelar, describiendo los modelos predictivos del mismo respecto al desarrollo psicológico y la inteligencia. Métodos: Hemos realizado un estudio observacional sobre 62 parejas de gemelos de 6 años de edad. Para ello se realizó una evaluación individual de cada uno de los niños con sus madres utilizando las baterías CUMANIN y K-BIT. Igualmente, se recogieron los datos clínicos perinatales. Realizamos un análisis estratificado y multivariante mediante regresión lineal múltiple. Resultados: El tipo de parto es la variable que mostró un mayor valor predictivo de las puntuaciones, de forma que los mejores resultados se obtuvieron en los niños nacidos por parto vaginal. Sin embargo, comparativamente, hemos observado la existencia de peores puntuaciones en los segundos gemelos nacidos por vía vaginal en las variables «estructuración espacial», «desarrollo no verbal» y «desarrollo total». Conclusiones: Las variables perinatales predicen los resultados a largo plazo en gemelos. La posible divergencia de intereses prenatales entre hermanos gemelos plantea la necesidad de individualizar cada caso y consensuar con los padres la actuación perinatal (AU)

Introduction: In recent years the incidence of multiple pregnancies has increased in our clinical settings. These mothers and their twin newborns are particularly vulnerable to neonatal mortality and morbidity due to their high rate of prematurity and perinatal complications. Long-term development outcomes have also to be considered. Objectives: To analyze the influence of the mode of delivery and other perinatal variables such as birth order, in the long-term development of twins, describing predictive models regarding psychological development and intelligence. Methods: We conducted an observational study in 62 pairs of 6-years-old twins. We assessed all children and their mothers, using CUMANIN and K-BIT batteries, and collected perinatal clinical data. We perform stratified and multivariate analysis using multiple linear regression. Results: The type of delivery was the variable that showed greater predictive value of the scores, so that the best results were obtained for children born vaginally. However, we have observed the existence of comparatively lower scores in the second twins born vaginally in some of the studied areas: spatial structuring, nonverbal development and overall development. Conclusions: Perinatal variables predict long-term outcomes in twins. Possible different prenatal interests of both co-twins make essential to provide information to parents in order to agree perinatal interventions (AU)

The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders.

Research into the causes of psychopathology has largely focused on two broad etiologic factors: genetic vulnerability and environmental stressors. An important role for familial/heritable factors in the etiology of a broad range of psychiatric disorders was established well before the modern era of genomic research. This review focuses on the genetic basis of three disorder categories-posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and the anxiety disorders-for which environmental stressors and stress responses are understood to be central to pathogenesis. Each of these disorders aggregates in families and is moderately heritable. More recently, molecular genetic approaches, including genome-wide studies of genetic variation, have been applied to identify specific risk variants. In this review, I summarize evidence for genetic contributions to PTSD, MDD, and the anxiety disorders including genetic epidemiology, the role of common genetic variation, the role of rare and structural variation, and the role of gene-environment interaction. Available data suggest that stress-related disorders are highly complex and polygenic and, despite substantial progress in other areas of psychiatric genetics, few risk loci have been identified for these disorders. Progress in this area will likely require analysis of much larger sample sizes than have been reported to date. The phenotypic complexity and genetic overlap among these disorders present further challenges. The review concludes with a discussion of prospects for clinical translation of genetic findings and future directions for research.

Adjusted inference procedures for the interobserver agreement in twin studies.

We propose adjusted inference procedures for evaluating the agreement/disagreement of two raters in a clustered setting involving twins or paired body parts. These procedures include the construction of a confidence interval for the kappa statistic, a related test of statistical significance and a formula that facilitates sample size estimation. The results of a simulation study suggest that a simple adjustment using an estimated design effect will provide valid inferences. The methods proposed are illustrated using an example from the literature.

Tabaco y cannabis / Smoking and cannabis

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Influencias genéticas y ambientales sobre el índice de masa corporal en una población española adolescente gemelar / Genetic and environmental contributions to body mass index in a Spanish adolescent twin sample

Fundamento y objetivo: Los estudios familiares y gemelares han demostrado que los factores genéticos son responsables del 47-90% de la variancia interindividual del índice de masa corporal (IMC). El objetivo de la presente investigación fue evaluar los factores genéticos y ambientales que contribuyen a las diferencias en el IMC, y en función del sexo, en una muestra gemelar de escolares de la Comunidad Valenciana. Material y método: Quinientas ochenta y cuatro parejas de gemelos de 13 a 18 años de edad completaron el estudio: 82 parejas monocigóticas (MC) y 87 dicigóticas (DC) varones, 118 (MC) y 102 (DC) mujeres, y 195 parejas (DC) de sexo opuesto. Para determinar la cigosidad, los profesores rellenaron un cuestionario de similitud física y pesaron y tallaron a los participantes. Se calculó el IMC y se estableció el estado nutricional según la edad. Se llevó a cabo una modelización del IMC que permitió establecer los componentes genéticos y ambientales (comunes y específicos) de su variancia. Resultados: Se observó un 7,1% de sobrepeso y un 2,8% de obesidad. La heredabilidad del IMC se estimó en un 88% en niños y en un 72,1% en niñas. Los factores ambientales específicos explicaron el resto de la variancia del IMC (en niños el 12% y en niñas el 8,8%). Solo en las niñas apareció una contribución de los factores ambientales comunes. Conclusiones: La influencia genética sobre el IMC es intensa durante la adolescencia, con ligeras variaciones en función del sexo, siendo solo las niñas vulnerables a las influencias ambientales comunes (AU)

Background and objective: Twin and family studies support large genetic influences on variability in body mass index (BMI), with heritability estimates ranging from 47% to over 90%. Our objective was to study the relative contributions of genetics and environment to BMI, evaluating sex differences, in an adolescent twin sample from Valencia, Spain. Material and methods: Five hundred eighty-four pairs of adolescent twins between 13 and 18 years of age completed the study (82 monozygotic [MZ] and 87 dizygotic [DZ] pairs of male twins, 118 MZ and 102 DZ pairs of female twins, and 195 opposite-sex pairs of DZ twins). To determine zygosity, teachers responded a questionnaire on physical similarity. They also measured the participant's height and weight. BMI was calculated and weight status was determined according to age. We used twin models to assess genetic and environmental (common and unique) factors affecting BMI. Results: There was a 7.1% frequency of overweight and 2.8% of obesity. The estimated heritability of BMI was 88.0% in boys and 72.1% in girls, with the remaining variance attributable to non-shared environment in boys (12.0%) and 8.8% in girls. It was only in girls that common environment had an effect on BMI. Conclusions: Genetics appears to play an important role in explaining the variability in BMI in the adolescence, with slight variations between boys and girls. Common environmental factors exert their influence on BMI only in girls (AU)