Integrated analysis of direct and proxy genome wide association studies highlights polygenicity of Alzheimer's disease outside of the APOE region.

Recent meta-analyses combining direct genome-wide association studies (GWAS) with those of family history (GWAX) have indicated very low SNP heritability of Alzheimer's disease (AD). These low estimates may call into question the prospects of continued progress in genetic discovery for AD within the spectrum of common variants. We highlight dramatic downward biases in previous methods, and we validate a novel method for the estimation of SNP heritability via integration of GWAS and GWAX summary data. We apply our method to investigate the genetic architecture of AD using GWAX from UK Biobank and direct case-control GWAS from the International Genomics of Alzheimer's Project (IGAP). We estimate the liability scale common variant SNP heritability of Clinical AD outside of APOE region at ~7-11%, and we project the corresponding estimate for AD pathology to be up to approximately 23%. We estimate that nearly 90% of common variant SNP heritability of Clinical AD exists outside the APOE region. Rare variants not tagged in standard GWAS may account for additional variance. Our results indicate that, while GWAX for AD in UK Biobank may result in greater attenuation of genetic effects beyond that conventionally assumed, it does not introduce appreciable contamination of signal by genetically distinct traits relative to direct case-control GWAS in IGAP. Genetic risk for AD represents a strong effect of APOE superimposed upon a highly polygenic background.

Disentangling potential causal effects of educational duration on well-being, and mental and physical health outcomes.

BACKGROUND: Extensive research has focused on the potential benefits of education on various mental and physical health outcomes. However, whether the associations reflect a causal effect is harder to establish. METHODS: To examine associations between educational duration and specific aspects of well-being, anxiety and mood disorders, and cardiovascular health in a sample of European Ancestry UK Biobank participants born in England and Wales, we apply four different causal inference methods (a natural policy experiment leveraging the minimum school-leaving age, a sibling-control design, Mendelian randomization [MR], and within-family MR), and assess if the methods converge on the same conclusion. RESULTS: A comparison of results across the four methods reveals that associations between educational duration and these outcomes appears predominantly to be the result of confounding or bias rather than a true causal effect of education on well-being and health outcomes. Although we do consistently find no associations between educational duration and happiness, family satisfaction, work satisfaction, meaning in life, anxiety, and bipolar disorder, we do not find consistent significant associations across all methods for the other phenotypes (health satisfaction, depression, financial satisfaction, friendship satisfaction, neuroticism, and cardiovascular outcomes). CONCLUSIONS: We discuss inconsistencies in results across methods considering their respective limitations and biases, and additionally discuss the generalizability of our findings in light of the sample and phenotype limitations. Overall, this study strengthens the idea that triangulation across different methods is necessary to enhance our understanding of the causal consequences of educational duration.

Ultra-rare and common genetic variant analysis converge to implicate negative selection and neuronal processes in the aetiology of schizophrenia.

Both common and rare genetic variants (minor allele frequency >1% and <0.1% respectively) have been implicated in the aetiology of schizophrenia. In this study, we integrate single-cell gene expression data with publicly available Genome-Wide Association Study (GWAS) and exome sequenced data in order to investigate in parallel, the enrichment of common and (ultra-)rare variants related to schizophrenia in several functionally relevant gene-sets. Four types of gene-sets were constructed 1) protein-truncating variant (PTV)-intolerant (PI) genes 2) genes expressed in brain cell types and neurons ascertained from mouse and human brain tissue 3) genes defined by synaptic function and location and 4) intersection genes, i.e., PI genes that are expressed in the human and mouse brain cell gene-sets. We show that common as well as ultra-rare schizophrenia-associated variants are overrepresented in PI genes, in excitatory neurons from the prefrontal cortex and hippocampus, medium spiny neurons, and genes enriched for synaptic processes. We also observed stronger enrichment in the intersection genes. Our findings suggest that across the allele frequency spectrum, genes and genetic variants likely to be under stringent selection, and those expressed in particular brain cell types, are involved in the same biological pathways influencing the risk for schizophrenia.

Multivariate analyses of molecular genetic associations between childhood psychopathology and adult mood disorders and related traits.

Ubiquitous associations have been detected between different types of childhood psychopathology and polygenic risk scores based on adult psychiatric disorders and related adult outcomes, indicating that genetic factors partly explain the association between childhood psychopathology and adult outcomes. However, these analyses in general do not take into account the correlations between the adult trait and disorder polygenic risk scores. This study aimed to further clarify the influence of genetic factors on associations between childhood psychopathology and adult outcomes by accounting for these correlations. Using a multivariate multivariable regression, we analyzed associations of childhood attention-deficit/hyperactivity disorder (ADHD), internalizing, and social problems, with polygenic scores (PGS) of adult disorders and traits including major depression, bipolar disorder, subjective well-being, neuroticism, insomnia, educational attainment, and body mass index (BMI), derived for 20,539 children aged 8.5-10.5 years. After correcting for correlations between the adult phenotypes, major depression PGS were associated with all three childhood traits, that is, ADHD, internalizing, and social problems. In addition, BMI PGS were associated with ADHD symptoms and social problems, while neuroticism PGS were only associated with internalizing problems and educational attainment PGS were only associated with ADHD symptoms. PGS of bipolar disorder, subjective well-being, and insomnia were not associated with any childhood traits. Our findings suggest that associations between childhood psychopathology and adult traits like insomnia and subjective well-being may be primarily driven by genetic factors that influence adult major depression. Additionally, specific childhood phenotypes are genetically associated with educational attainment, BMI and neuroticism.

Onset of Preclinical Alzheimer Disease in Monozygotic Twins.

OBJECTIVE: The present work was undertaken to study the genetic contribution to the start of Alzheimer's disease (AD) with amyloid and tau biomarkers in cognitively intact older identical twins. METHODS: We studied in 96 monozygotic twin-pairs relationships between amyloid-beta (Aß) aggregation as measured by the Aß1-42/1-40 ratio in cerebrospinal fluid (CSF; n = 126) and positron emission tomography (PET, n = 194), and CSF markers for Aß production (beta-secretase 1, Aß1-40, and Aß1-38) and CSF tau. Associations among markers were tested with generalized estimating equations including a random effect for twin status, adjusted for age, gender, and apolipoprotein E ε4 genotype. We used twin analyses to determine relative contributions of genetic and/or environmental factors to AD pathophysiological processes. RESULTS: Twenty-seven individuals (14%) had an abnormal amyloid PET, and 14 twin-pairs (15%) showed discordant amyloid PET scans. Within twin-pairs, Aß production markers and total-tau (t-tau) levels strongly correlated (r range = 0.73-0.86, all p < 0.0001), and Aß aggregation markers and 181-phosphorylated-tau (p-tau) levels correlated moderately strongly (r range = 0.50-0.64, all p < 0.0001). Cross-twin cross-trait analysis showed that Aß1-38 in one twin correlated with Aß1-42/1-40 ratios, and t-tau and p-tau levels in their cotwins (r range = -0.28 to 0.58, all p < .007). Within-pair differences in Aß production markers related to differences in tau levels (r range = 0.49-0.61, all p < 0.0001). Twin discordance analyses suggest that Aß production and tau levels show coordinated increases in very early AD. INTERPRETATION: Our results suggest a substantial genetic/shared environmental background contributes to both Aß and tau increases, suggesting that modulation of environmental risk factors may aid in delaying the onset of AD pathophysiological processes. ANN NEUROL 2021;89:987-1000.

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness.

Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.

Continuity of Genetic Risk for Aggressive Behavior Across the Life-Course.

We test whether genetic influences that explain individual differences in aggression in early life also explain individual differences across the life-course. In two cohorts from The Netherlands (N = 13,471) and Australia (N = 5628), polygenic scores (PGSs) were computed based on a genome-wide meta-analysis of childhood/adolescence aggression. In a novel analytic approach, we ran a mixed effects model for each age (Netherlands: 12-70 years, Australia: 16-73 years), with observations at the focus age weighted as 1, and decaying weights for ages further away. We call this approach a 'rolling weights' model. In The Netherlands, the estimated effect of the PGS was relatively similar from age 12 to age 41, and decreased from age 41-70. In Australia, there was a peak in the effect of the PGS around age 40 years. These results are a first indication from a molecular genetics perspective that genetic influences on aggressive behavior that are expressed in childhood continue to play a role later in life.

Safe Linkage of Cohort and Population-Based Register Data in a Genomewide Association Study on Health Care Expenditure.

There are research questions whose answers require record linkage of multiple databases that may be characterized by limited options for full data sharing. For this purpose, the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) consortium has supported the development of the ODISSEI Secure Supercomputer (OSSC) platform that allows researchers to link cohort data to data from Statistics Netherlands and run large-scale analyses in a high-performance computing (HPC) environment. Here, we report a successful record linkage genomewide association (GWA) study on expenditure for total health, mental health, primary and hospital care, and medication. Record linkage for genotype data from 16,726 participants from the Netherlands Twin Register (NTR) with data from Statistics Netherlands was accomplished in the secure OSSC platform, followed by gene-based tests and estimation of total and single nucleotide polymorphism (SNP)-based heritability. The total heritability of expenditure ranged between 29.4% (SE 0.8) and 37.5% (SE 0.8), but GWA analyses did not identify SNPs or genes that were genomewide significantly associated with health care expenditure. SNP-based heritability was between 0.0% (SE 3.5) and 5.4% (SE 4.0) and was different from zero for mental health care and primary care expenditure. We conclude that successfully linking genotype data to administrative health care expenditure data from Statistics Netherlands is feasible and demonstrates a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analyzing linked data in large scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions.

Content, diagnostic, correlational, and genetic similarities between common measures of childhood aggressive behaviors and related psychiatric traits.

BACKGROUND: Given the role of childhood aggressive behavior (AGG) in everyday child development, precise and accurate measurement is critical in clinical practice and research. This study aims to quantify agreement among widely used measures of childhood AGG regarding item content, clinical concordance, correlation, and underlying genetic construct. METHODS: We analyzed data from 1254 Dutch twin pairs (age 8-10 years, 51.1% boys) from a general population sample for whom both parents completed the A-TAC, CBCL, and SDQ at the same occasion. RESULTS: There was substantial variation in item content among AGG measures, ranging from .00 (i.e., mutually exclusive) to .50 (moderate agreement). Clinical concordance (i.e., do the same children score above a clinical threshold among AGG measures) was very weak to moderate with estimates ranging between .01 and .43 for mother-reports and between .12 and .42 for father-reports. Correlations among scales were weak to strong, ranging from .32 to .70 for mother-reports and from .32 to .64 for father-reports. We found weak to very strong genetic correlations among the measures, with estimates between .65 and .84 for mother-reports and between .30 and .87 for father-reports. CONCLUSIONS: Our results demonstrated that degree of agreement between measures of AGG depends on the type (i.e., item content, clinical concordance, correlation, genetic correlation) of agreement considered. Because agreement was higher for correlations compared to clinical concordance (i.e., above or below a clinical cutoff), we propose the use of continuous scores to assess AGG, especially for combining data with different measures. Although item content can be different and agreement among observed measures may not be high, the genetic correlations indicate that the underlying genetic liability for childhood AGG is consistent across measures.

Conditional eQTL analysis reveals allelic heterogeneity of gene expression.

In recent years, multiple eQTL (expression quantitative trait loci) catalogs have become available that can help understand the functionality of complex trait-related single nucleotide polymorphisms (SNPs). In eQTL catalogs, gene expression is often strongly associated with multiple SNPs, which may reflect either one or multiple independent associations. Conditional eQTL analysis allows a distinction between dependent and independent eQTLs. We performed conditional eQTL analysis in 4,896 peripheral blood microarray gene expression samples. Our analysis showed that 35% of genes with a cis eQTL have at least two independent cis eQTLs; for several genes up to 13 independent cis eQTLs were identified. Also, 12% (671) of the independent cis eQTLs identified in conditional analyses were not significant in unconditional analyses. The number of GWAS catalog SNPs identified as eQTL in the conditional analyses increases with 24% as compared to unconditional analyses. We provide an online conditional cis eQTL mapping catalog for whole blood (https://eqtl.onderzoek.io/), which can be used to lookup eQTLs more accurately than in standard unconditional whole blood eQTL databases.

GWIS: Genome-Wide Inferred Statistics for Functions of Multiple Phenotypes.

Here we present a method of genome-wide inferred study (GWIS) that provides an approximation of genome-wide association study (GWAS) summary statistics for a variable that is a function of phenotypes for which GWAS summary statistics, phenotypic means, and covariances are available. A GWIS can be performed regardless of sample overlap between the GWAS of the phenotypes on which the function depends. Because a GWIS provides association estimates and their standard errors for each SNP, a GWIS can form the basis for polygenic risk scoring, LD score regression, Mendelian randomization studies, biological annotation, and other analyses. GWISs can also be used to boost power of a GWAS meta-analysis where cohorts have not measured all constituent phenotypes in the function. We demonstrate the accuracy of a BMI GWIS by performing power simulations and type I error simulations under varying circumstances, and we apply a GWIS by reconstructing a body mass index (BMI) GWAS based on a weight GWAS and a height GWAS. Furthermore, we apply a GWIS to further our understanding of the underlying genetic structure of bipolar disorder and schizophrenia and their relation to educational attainment. Our analyses suggest that the previously reported genetic correlation between schizophrenia and educational attainment is probably induced by the observed genetic correlation between schizophrenia and bipolar disorder and the previously reported genetic correlation between bipolar disorder and educational attainment.

Associations between loneliness and personality are mostly driven by a genetic association with Neuroticism.

OBJECTIVE: Loneliness is an aversive response to a discrepancy between desired and actual social relationships and correlates with personality. We investigate the relationship of loneliness and personality in twin family and molecular genetic data. METHOD: Phenotypic correlations between loneliness and the Big Five personality traits were estimated in 29,625 adults, and in a group with genome-wide genotype data (N = 4,222), genetic correlations were obtained. We explored whether genetic correlations may reflect causal relationships by investigating within monozygotic twin pair differences (Npairs = 2,662), by longitudinal within-subject changes in personality and loneliness (N = 4,260-9,238 longitudinal comparisons), and by longitudinal cross-lagged panel analyses (N = 15,628). Finally, we tested whether genetic correlations were due to cross-trait assortative mating (Nspouse pairs = 4,436). RESULTS: The strongest correlations with loneliness were observed for Neuroticism (r = .55) and Extraversion (r = -.33). Only Neuroticism showed a high correlation with loneliness independent of other personality traits (r = .50), so follow-up analyses focused on Neuroticism. The genetic correlation between loneliness and Neuroticism from genotyped variants was .71; a significant reciprocal causal relationship and nonsignificant cross-trait assortative mating imply that this is at least partly due to mediated pleiotropy. CONCLUSIONS: We show that the relationship between loneliness and personality is largely explained by its relationship with Neuroticism, which is substantially genetic in nature.

Characterizing the Relation Between Expression QTLs and Complex Traits: Exploring the Role of Tissue Specificity.

Measurement of gene expression levels and detection of eQTLs (expression quantitative trait loci) are difficult in tissues with limited sample availability, such as the brain. However, eQTL overlap between tissues might be high, which would allow for inference of eQTL functioning in the brain via eQTLs detected in readily accessible tissues, e.g. whole blood. Applying Stratified Linkage Disequilibrium Score Regression (SLDSR), we quantified the enrichment in polygenic signal of blood and brain eQTLs in genome-wide association studies (GWAS) of 11 complex traits. We looked at eQTLs discovered in 44 tissues by the Genotype-Tissue Expression (GTEx) consortium and two other large representative studies, and found no tissue-specific eQTL effects. Next, we integrated the GTEx eQTLs with regions associated with tissue-specific histone modifiers, and interrogated their effect on rheumatoid arthritis and schizophrenia. We observed substantially enriched effects of eQTLs located inside regions bearing modification H3K4me1 on schizophrenia, but not rheumatoid arthritis, and not tissue-specific. Finally, we extracted eQTLs associated with tissue-specific differentially expressed genes and determined their effects on rheumatoid arthritis and schizophrenia, these analysis revealed limited enrichment of eQTLs associated with gene specifically expressed in specific tissues. Our results pointed to strong enrichment of eQTLs in their effect on complex traits, without evidence for tissue-specific effects. Lack of tissue-specificity can be either due to a lack of statistical power or due to the true absence of tissue-specific effects. We conclude that eQTLs are strongly enriched in GWAS signal and that the enrichment is not specific to the eQTL discovery tissue. Until sample sizes for eQTL discovery grow sufficiently large, working with relatively accessible tissues as proxy for eQTL discovery is sensible and restricting lookups for GWAS hits to a specific tissue for which limited samples are available might not be advisable.

Heritability of Behavioral Problems in 7-Year Olds Based on Shared and Unique Aspects of Parental Views.

In studies of child psychopathology, phenotypes of interest are often obtained by parental ratings. When behavioral ratings are obtained in the context of a twin study, this allows for the decomposition of the phenotypic variance, into a genetic and a non-genetic part. If a phenotype is assessed by a single rater, heritability is based on the child's behavior as expressed in the presence of that particular rater, whereas heritability based on assessments by multiple raters allows for the estimation of the heritability of the phenotype based on rater agreement, as well as the heritability of the rater specific view of the behavior. The aim of this twin study was to quantify the rater common and rater specific contributions to the variation in children's behavioral problems. We estimated the heritability of maternal and paternal ratings of the Child Behavior Checklist (CBCL) 6-18 empirical emotional and behavioral problem scales in a large sample of 12,310 7-year old Dutch twin pairs. Between 30 and 59% of variation in the part of the phenotype parents agree upon was explained by genetic effects. Common environmental effects that make children in the same family similar explained less variance, ranging between 0 and 32%. For unique views of their children's behavioral problems, heritability ranged between 0 and 20% for maternal and between 0 and 22% for paternal views. Between 7 and 24% of the variance was accounted for by common environmental factors specific to mother and father's views. The proportion of rater shared and rater specific heritability can be translated into genetic correlations between parental views and inform the design and interpretation of results of molecular genetic studies. Genetic correlations were nearly or above 0.7 for all CBCL based psychopathology scales. Such large genetic correlations suggest two practical guidelines for genome-wide association studies (GWAS): when studies have collected data from either fathers or mothers, the shared genetic aetiology in parental ratings indicates that is possible to analyze paternal and maternal assessments in a single GWAS or meta-analysis. Secondly, if a study has collected information from both parents, a gain in statistical power may be realized in GWAS by the simultaneous analysis of the data.

Joint developmental trajectories of internalizing and externalizing disorders between childhood and adolescence.

This study sought to identify trajectories of DSM-IV based internalizing (INT) and externalizing (EXT) problem scores across childhood and adolescence and to provide insight into the comorbidity by modeling the co-occurrence of INT and EXT trajectories. INT and EXT were measured repeatedly between age 7 and age 15 years in over 7,000 children and analyzed using growth mixture models. Five trajectories were identified for both INT and EXT, including very low, low, decreasing, and increasing trajectories. In addition, an adolescent onset trajectory was identified for INT and a stable high trajectory was identified for EXT. Multinomial regression showed that similar EXT and INT trajectories were associated. However, the adolescent onset INT trajectory was independent of high EXT trajectories, and persisting EXT was mainly associated with decreasing INT. Sex and early life environmental risk factors predicted EXT and, to a lesser extent, INT trajectories. The association between trajectories indicates the need to consider comorbidity when a child presents with INT or EXT disorders, particularly when symptoms start early. This is less necessary when INT symptoms start at adolescence. Future studies should investigate the etiology of co-occurring INT and EXT and the specific treatment needs of these severely affected children.

Smoking and caffeine consumption: a genetic analysis of their association.

Smoking and caffeine consumption show a strong positive correlation, but the mechanism underlying this association is unclear. Explanations include shared genetic/environmental factors or causal effects. This study employed three methods to investigate the association between smoking and caffeine. First, bivariate genetic models were applied to data of 10 368 twins from the Netherlands Twin Register in order to estimate genetic and environmental correlations between smoking and caffeine use. Second, from the summary statistics of meta-analyses of genome-wide association studies on smoking and caffeine, the genetic correlation was calculated by LD-score regression. Third, causal effects were tested using Mendelian randomization analysis in 6605 Netherlands Twin Register participants and 5714 women from the Avon Longitudinal Study of Parents and Children. Through twin modelling, a genetic correlation of r0.47 and an environmental correlation of r0.30 were estimated between current smoking (yes/no) and coffee use (high/low). Between current smoking and total caffeine use, this was r0.44 and r0.00, respectively. LD-score regression also indicated sizeable genetic correlations between smoking and coffee use (r0.44 between smoking heaviness and cups of coffee per day, r0.28 between smoking initiation and coffee use and r0.25 between smoking persistence and coffee use). Consistent with the relatively high genetic correlations and lower environmental correlations, Mendelian randomization provided no evidence for causal effects of smoking on caffeine or vice versa. Genetic factors thus explain most of the association between smoking and caffeine consumption. These findings suggest that quitting smoking may be more difficult for heavy caffeine consumers, given their genetic susceptibility.

Psychopathology in 7-year-old children: Differences in maternal and paternal ratings and the genetic epidemiology.

The assessment of children's psychopathology is often based on parental report. Earlier studies have suggested that rater bias can affect the estimates of genetic, shared environmental and unique environmental influences on differences between children. The availability of a large dataset of maternal as well as paternal ratings of psychopathology in 7-year old children enabled (i) the analysis of informant effects on these assessments, and (ii) to obtain more reliable estimates of the genetic and non-genetic effects. DSM-oriented measures of affective, anxiety, somatic, attention-deficit/hyperactivity, oppositional-defiant, conduct, and obsessive-compulsive problems were rated for 12,310 twin pairs from the Netherlands Twin Register by mothers (N = 12,085) and fathers (N = 8,516). The effects of genetic and non-genetic effects were estimated on the common and rater-specific variance. For all scales, mean scores on maternal ratings exceeded paternal ratings. Parents largely agreed on the ranking of their child's problems (r 0.60-0.75). The heritability was estimated over 55% for maternal and paternal ratings for all scales, except for conduct problems (44-46%). Unbiased shared environmental influences, i.e., on the common variance, were significant for affective (13%), oppositional (13%), and conduct problems (37%). In clinical settings, different cutoffs for (sub)clinical scores could be applied to paternal and maternal ratings of their child's psychopathology. Only for conduct problems, shared environmental and genetic influences explain an equal amount in differences between children. For the other scales, genetic factors explain the majority of the variance, especially for the common part that is free of rater bias. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Evidence for Gender-Dependent Genotype by Environment Interaction in Adult Depression.

Depression in adults is heritable with about 40 % of the phenotypic variance due to additive genetic effects and the remaining phenotypic variance due to unique (unshared) environmental effects. Common environmental effects shared by family members are rarely found in adults. One possible explanation for this finding is that there is an interaction between genes and the environment which may mask effects of the common environment. To test this hypothesis, we investigated genotype by environment interaction in a large sample of female and male adult twins aged 18-70 years. The anxious depression subscale of the Adult Self Report from the Achenbach System of Empirically Based Assessment (Achenbach and Rescorla in Manual for the ASEBA adult: forms and profiles, 2003) was completed by 13,022 twins who participate in longitudinal studies of the Netherlands Twin Register. In a single group analysis, we found genotype by unique environment interaction, but no genotype by common environment interaction. However, when conditioning on gender, we observed genotype by common environment interaction in men, with larger common environmental variance in men who are genetically less at risk to develop depression. Although the effect size of the interaction is characterized by large uncertainty, the results show that there is at least some variance due to the common environment in adult depression in men.

A genome-wide approach to children's aggressive behavior: The EAGLE consortium.

Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of aggressive behavior in children. We analyzed data from nine population-based studies and assessed aggressive behavior using well-validated parent-reported questionnaires. This is the largest sample exploring children's aggressive behavior to date (N = 18,988), with measures in two developmental stages (N = 15,668 early childhood and N = 16,311 middle childhood/early adolescence). First, we estimated the additive genetic variance of children's aggressive behavior based on genome-wide SNP information, using genome-wide complex trait analysis (GCTA). Second, genetic associations within each study were assessed using a quasi-Poisson regression approach, capturing the highly right-skewed distribution of aggressive behavior. Third, we performed meta-analyses of genome-wide associations for both the total age-mixed sample and the two developmental stages. Finally, we performed a gene-based test using the summary statistics of the total sample. GCTA quantified variance tagged by common SNPs (10-54%). The meta-analysis of the total sample identified one region in chromosome 2 (2p12) at near genome-wide significance (top SNP rs11126630, P = 5.30 × 10(-8) ). The separate meta-analyses of the two developmental stages revealed suggestive evidence of association at the same locus. The gene-based analysis indicated association of variation within AVPR1A with aggressive behavior. We conclude that common variants at 2p12 show suggestive evidence for association with childhood aggression. Replication of these initial findings is needed, and further studies should clarify its biological meaning. © 2015 Wiley Periodicals, Inc.

Genetic and Environmental Stability of Neuroticism From Adolescence to Adulthood.

Longitudinal studies of neuroticism have shown that, on average, neuroticism scores decrease from adolescence to adulthood. The heritability of neuroticism is estimated between 0.30 and 0.60 and does not seem to vary greatly as a function of age. Shared environmental effects are rarely reported. Less is known about the role of genetic and environmental influences on the rank order stability of neuroticism in the period from adolescence to adulthood. We studied the stability of neuroticism in a cohort sequential (classical) twin design, from adolescence (age 14 years) to young adulthood (age 32 years). A genetic simplex model that was fitted to the longitudinal neuroticism data showed that the genetic stability of neuroticism was relatively high (genetic correlations between adjacent age bins >0.9), and increased from adolescence to adulthood. Environmental stability was appreciably lower (environmental correlations between adjacent age bins were between 0.3 and 0.6). This low stability was largely due to age-specific environmental variance, which was dominated by measurement error. This attenuated the age-to-age environmental correlations. We constructed an environmental covariance matrix corrected for this error, under the strong assumption that all age-specific environmental variance is error variance. The environmental (co)variance matrix corrected for attenuation revealed highly stable environmental influences on neuroticism (correlations between adjacent age bins were between 0.7 and 0.9). Our results indicate that both genetic and environmental influences have enduring effects on individual differences in neuroticism.