Where you live matters: visualizing environmental effects on reading attainment.

BACKGROUND: The way in which socioeconomic status (SES) moderates the etiology of reading attainment has been explored many times, with past work often finding that genetic influences are suppressed under conditions of socioeconomic deprivation and more fully realized under conditions of socioeconomic advantage: a gene-SES interaction. Additionally, past work has pointed toward the presence of gene-location interactions, with the relative influence of genes and environment varying across geographic regions of the same country/state. METHOD: This study investigates the extent to which SES and geographical location interact to moderate the genetic and environmental components of reading attainment. Utilizing data from 2,135 twin pairs in Florida (mean age 13.82 years, range 10.71-17.77), the study operationalized reading attainment as reading comprehension scores from a statewide test and SES as household income. We applied a spatial twin analysis procedure to investigate how twin genetic and environmental estimates vary by geographic location. We then expanded this analysis to explore how the moderating role of SES on said genetic and environmental influences also varied by geographic location. RESULTS: A gene-SES interaction was found, with heritability of reading being suppressed in lower- (23%) versus higher-SES homes (78%). The magnitude of the moderating parameters were not consistent by location, however, and ranged from -0.10 to 0.10 for the moderating effect on genetic influences, and from -0.30 to 0.05 for the moderating effect on environmental influences. For smaller areas and those with less socioeconomic variability, the magnitude of the genetic moderating parameter was high, giving rise to more fully realized genetic influences on reading there. CONCLUSIONS: SES significantly influences reading variability. However, a child's home location matters in both the overall etiology and how strongly SES moderates said etiologies. These results point toward the presence of multiple significant environmental factors that simultaneously, and inseparably, influence the underlying etiology of reading attainment.

Methodologies for Monitoring Mental Health on Twitter: Systematic Review.

BACKGROUND: The use of social media data to predict mental health outcomes has the potential to allow for the continuous monitoring of mental health and well-being and provide timely information that can supplement traditional clinical assessments. However, it is crucial that the methodologies used to create models for this purpose are of high quality from both a mental health and machine learning perspective. Twitter has been a popular choice of social media because of the accessibility of its data, but access to big data sets is not a guarantee of robust results. OBJECTIVE: This study aims to review the current methodologies used in the literature for predicting mental health outcomes from Twitter data, with a focus on the quality of the underlying mental health data and the machine learning methods used. METHODS: A systematic search was performed across 6 databases, using keywords related to mental health disorders, algorithms, and social media. In total, 2759 records were screened, of which 164 (5.94%) papers were analyzed. Information about methodologies for data acquisition, preprocessing, model creation, and validation was collected, as well as information about replicability and ethical considerations. RESULTS: The 164 studies reviewed used 119 primary data sets. There were an additional 8 data sets identified that were not described in enough detail to include, and 6.1% (10/164) of the papers did not describe their data sets at all. Of these 119 data sets, only 16 (13.4%) had access to ground truth data (ie, known characteristics) about the mental health disorders of social media users. The other 86.6% (103/119) of data sets collected data by searching keywords or phrases, which may not be representative of patterns of Twitter use for those with mental health disorders. The annotation of mental health disorders for classification labels was variable, and 57.1% (68/119) of the data sets had no ground truth or clinical input on this annotation. Despite being a common mental health disorder, anxiety received little attention. CONCLUSIONS: The sharing of high-quality ground truth data sets is crucial for the development of trustworthy algorithms that have clinical and research utility. Further collaboration across disciplines and contexts is encouraged to better understand what types of predictions will be useful in supporting the management and identification of mental health disorders. A series of recommendations for researchers in this field and for the wider research community are made, with the aim of enhancing the quality and utility of future outputs.

Epicosm-a framework for linking online social media in epidemiological cohorts.

MOTIVATION: Social media represent an unrivalled opportunity for epidemiological cohorts to collect large amounts of high-resolution time course data on mental health. Equally, the high-quality data held by epidemiological cohorts could greatly benefit social media research as a source of ground truth for validating digital phenotyping algorithms. However, there is currently a lack of software for doing this in a secure and acceptable manner. We worked with cohort leaders and participants to co-design an open-source, robust and expandable software framework for gathering social media data in epidemiological cohorts. IMPLEMENTATION: Epicosm is implemented as a Python framework that is straightforward to deploy and run inside a cohort's data safe haven. GENERAL FEATURES: The software regularly gathers Tweets from a list of accounts and stores them in a database for linking to existing cohort data. AVAILABILITY: This open-source software is freely available at [https://dynamicgenetics.github.io/Epicosm/].

A Polygenic Approach to Understanding Resilience to Peer Victimisation.

Previous studies suggest an individual's risk of depression following adversity may be moderated by their genetic liability. No study, however, has examined peer victimisation, an experience repeatedly associated with mental illness. We explore whether the negative mental health outcomes following victimisation can be partly attributed to genetic factors using polygenic scores for depression and wellbeing. Among participants from the Avon Longitudinal Study of Parents and Children (ALSPAC), we show that polygenic scores and peer victimisation are significant independent predictors of depressive symptoms (n=2268) and wellbeing (n=2299) in early adulthood. When testing for interaction effects, our results lead us to conclude that low mental health and wellbeing following peer victimisation is unlikely to be explained by a moderating effect of genetic factors, as indexed by current polygenic scores. Genetic profiling is therefore unlikely to be effective in identifying those more vulnerable to the effects of victimisation at present. The reasons why some go on to experience mental health problems following victimisation, while others remain resilient, requires further exploration, but our results rule out a major influence of current polygenic scores.

Peer victimisation during adolescence and its impact on wellbeing in adulthood: a prospective cohort study.

BACKGROUND: Peer victimisation is a common occurrence and has well-established links with a range of psychiatric problems in adulthood. Significantly less is known however, about how victimisation influences positive aspects of mental health such as wellbeing. The purpose of this study was therefore to assess for the first time, whether peer victimisation in adolescence is associated with adult wellbeing. We aimed to understand whether individuals who avoid a diagnosis of depression after victimisation, maintain good wellbeing in later life, and therefore display resilience. METHODS: Longitudinal data was taken from the Avon Longitudinal Study of Parents and Children, a prospective cohort study based in the UK. Peer victimisation was assessed at 13 years using a modified version of the bullying and friendship interview schedule, and wellbeing at age 23 using the Warwick-Edinburgh Mental Well-Being Scale. The presence or absence of depression was diagnosed using the Clinical Interview Schedule-Revised at 18 years. A series of logistic and linear regression analyses were used to explore relationships between peer victimisation, depression, and wellbeing, adjusting for potentially confounding individual and family factors. RESULTS: Just over 15% of victims of frequent bullying had a diagnosis of depression at age 18. Victimisation also had a significant impact on wellbeing, with a one-point increase in frequent victimisation associated with a 2.71-point (SE = 0.46, p < 0.001) decrease in wellbeing scores aged 23. This finding remained after adjustment for the mediating and moderating effects of depression, suggesting that the burden of victimisation extends beyond depression to impact wellbeing. Results therefore show that individuals who remain partially resilient by avoiding a diagnosis of depression after victimisation have significantly poorer wellbeing than their non-victimised counterparts. CONCLUSION: Overall, our study demonstrates for the first time that victimisation during adolescence is a significant risk factor for not only the onset of depression, but also poor wellbeing in adulthood. Such findings highlight the importance of investigating both dimensions of mental health to understand the true burden of victimisation and subsequent resilience. In addition to the need for interventions that reduce the likelihood of depression following adolescent victimisation, efforts should also be made to promote good wellbeing.

Mapping the genetic and environmental aetiology of autistic traits in Sweden and the United Kingdom.

Background: Autistic traits are influenced by both genetic and environmental factors, and are known to vary geographically in prevalence. But to what extent does their aetiology also vary from place to place? Methods: We applied a novel spatial approach to data on autistic traits from two large twin studies, the Child and Adolescent Twin Study in Sweden (CATSS; N = 16,677, including 8307 twin pairs) and the Twins Early Development Study in the UK (TEDS; N = 11,594, including 5796 twin pairs), to explore how the influence of nature and nurture on autistic traits varies from place to place. Results: We present maps of gene- and environment- by geography interactions in Sweden and the United Kingdom (UK), showing geographical variation in both genetic and environmental influences across the two countries. In Sweden genetic influences appear higher in the far south and in a band running across the centre of the country. Environmental influences appear greatest in the south and north, with reduced environmental influence across the central band. In the UK genetic influences appear greater in the south, particularly in more central southern areas and the southeast, the Midlands and the north of England. Environmental influences appear greatest in the south and east of the UK, with less influence in the north and the west. Conclusions: We hope this systematic approach to identifying aetiological interactions will inspire research to examine a wider range of previously unknown environmental influences on the aetiology of autistic traits. By doing so, we will gain greater understanding of how these environments draw out or mask genetic predisposition and interact with other environmental influences in the development of autistic traits.

Positive wellbeing and resilience following adolescent victimisation: An exploration into protective factors across development.

Background: Not all victims of bullying go on to develop problems with their mental health. To understand factors that may confer resilience, many have explored the moderating role of protective factors in relation to mental illness. No study to date, however, has considered moderators of adult wellbeing following victimisation. We explore 14 protective factors and test whether these promote good adult wellbeing in addition to prevent mental illness following victimisation. In doing so, we aimed to understand how positive mental health and resilience can be promoted. Methods: Data were derived from the Avon Longitudinal Study of Parents and Children. Participants were assessed for wellbeing and depressive symptoms at age 23, as well as victimisation in adolescence, and protective factors across development. Protective factors were categorised into individual-, family- and peer-level, and included factors like social skills, perceived school competence, and relationships with family and peers. The moderating role of the protective factors were examined using interactive regression models. Results: Perceived scholastic competence was the only factor that mitigated some of the negative effects of victimisation. Individuals with higher perceptions of scholastic competence had higher wellbeing in adulthood than victims with lower perceptions of competence. No protective factors positively moderated life satisfaction or the risk of depressive symptoms; although findings suggest that friendships in late adolescence may be protective for individuals exposed to less frequent victimisation. Conclusions: Our study is the first to explore a wide range of protective factors in predicting adult wellbeing following victimisation. We identify factors involved specifically in supporting wellbeing but not in reducing the risk of depression. Findings suggest that interventions aimed at increasing perceptions of scholastic competence in childhood may help to support more positive wellbeing in adulthood.

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.

Views on social media and its linkage to longitudinal data from two generations of a UK cohort study.

Background: Cohort studies gather huge volumes of information about a range of phenotypes but new sources of information such as social media data are yet to be integrated. Participant's long-term engagement with cohort studies, as well as the potential for their social media data to be linked to other longitudinal data, could provide novel advances but may also give participants a unique perspective on the acceptability of this growing research area. Methods: Two focus groups explored participant views towards the acceptability and best practice for the collection of social media data for research purposes. Participants were drawn from the Avon Longitudinal Study of Parents and Children cohort; individuals from the index cohort of young people (N=9) and from the parent generation (N=5) took part in two separate 90-minute focus groups. The discussions were audio recorded and subjected to qualitative analysis. Results: Participants were generally supportive of the collection of social media data to facilitate health and social research. They felt that their trust in the cohort study would encourage them to do so. Concern was expressed about the collection of data from friends or connections who had not consented. In terms of best practice for collecting the data, participants generally preferred the use of anonymous data derived from social media to be shared with researchers. Conclusion: Cohort studies have trusting relationships with their participants; for this relationship to extend to linking their social media data with longitudinal information, procedural safeguards are needed. Participants understand the goals and potential of research integrating social media data into cohort studies, but further research is required on the acquisition of their friend's data. The views gathered from participants provide important guidance for future work seeking to integrate social media in cohort studies.

The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers.

BACKGROUND: DNA methylation is associated with body mass index (BMI), but it is not clear if methylation scores are biomarkers for extant BMI or predictive of future BMI. Here, we explore the causal nature and predictive utility of DNA methylation measured in peripheral blood with BMI and cardiometabolic traits. METHODS: Analyses were conducted across the life course using the ARIES cohort of mothers (n = 792) and children (n = 906), for whom DNA methylation and genetic profiles and BMI at multiple time points (3 in children at birth, in childhood and in adolescence; 2 in mothers during pregnancy and in middle age) were available. Genetic and DNA methylation scores for BMI were derived using published associations between BMI and DNA methylation and genotype. Causal relationships between methylation and BMI were assessed using Mendelian randomisation and cross-lagged models. RESULTS: The DNA methylation scores in adult women explained 10% of extant BMI variance. However, less extant variance was explained by scores generated in the same women during pregnancy (2% BMI variance) and in older children (15-17 years; 3% BMI variance). Similarly, little extant variance was explained in younger children (at birth and at 7 years; 1% and 2%, respectively). These associations remained following adjustment for smoking exposure and education levels. The DNA methylation score was found to be a poor predictor of future BMI using linear and cross-lagged models, suggesting that DNA methylation variation does not cause later variation in BMI. However, there was some evidence to suggest that BMI is predictive of later DNA methylation. Mendelian randomisation analyses also support this direction of effect, although evidence is weak. Finally, we find that DNA methylation scores for BMI are associated with extant cardiometabolic traits independently of BMI and genetic score. CONCLUSION: The age-specific nature of DNA methylation associations with BMI, lack of causal relationship and limited predictive ability of future BMI indicate that DNA methylation is likely influenced by BMI and might more accurately be considered a biomarker of BMI and related outcomes rather than a predictor. Future epigenome-wide association studies may benefit from further examining associations between early DNA methylation and later health outcomes.

Participant acceptability of digital footprint data collection strategies: an exemplar approach to participant engagement and involvement in the ALSPAC birth cohort study.

Introduction: Digital footprint records - the tracks and traces amassed by individuals as a result of their interactions with the internet, digital devices and services - can provide ecologically valid data on individual behaviours. These could enhance longitudinal population study databanks; but few UK longitudinal studies are attempting this. When using novel sources of data, study managers must engage with participants in order to develop ethical data processing frameworks that facilitate data sharing whilst safeguarding participant interests. Objectives: This paper aims to summarise the participant involvement approach used by the ALSPAC birth cohort study to inform the development of a framework for using linked participant digital footprint data, and provide an exemplar for other data linkage infrastructures. Methods: The paper synthesises five qualitative forms of inquiry. Thematic analysis was used to code transcripts for common themes in relation to conditions associated with the acceptability of sharing digital footprint data for longitudinal research. Results: We identified six themes: participant understanding; sensitivity of location data; concerns for third parties; clarity on data granularity; mechanisms of data sharing and consent; and trustworthiness of the organisation. For cohort members to consider the sharing of digital footprint data acceptable, they require information about the value, validity and risks; control over sharing elements of the data they consider sensitive; appropriate mechanisms to authorise or object to their records being used; and trust in the organisation. Conclusion: Realising the potential for using digital footprint records within longitudinal research will be subject to ensuring that this use of personal data is acceptable; and that rigorously controlled population data science benefiting the public good is distinguishable from the misuse and lack of personal control of similar data within other settings. Participant co-development informs the ethical-governance framework for these novel linkages in a manner which is acceptable and does not undermine the role of the trusted data custodian.

Schizophrenia liability shares common molecular genetic risk factors with sleep duration and nightmares in childhood.

Background: Sleep abnormalities are common in schizophrenia, often appearing before psychosis onset; however, the mechanisms behind this are uncertain. We investigated whether genetic risk for schizophrenia is associated with sleep phenotypes. Methods: We used data from 6,058 children and 2,302 mothers from the Avon Longitudinal Study of Parents and Children (ALSPAC). We examined associations between a polygenic risk score for schizophrenia and sleep duration in both children and mothers, and nightmares in children, along with genetic covariances between these traits. Results: Polygenic risk for schizophrenia was associated with increased risk of nightmares (OR=1.07, 95% CI: 1.01, 1.14, p=0.02) in children, and also with less sleep (ß=-44.52, 95% CI: -88.98, -0.07; p=0.05). We observed a similar relationship with sleep duration in mothers, although evidence was much weaker (p=0.38). Finally, we found evidence of genetic covariance between schizophrenia risk and reduced sleep duration in children and mothers, and between schizophrenia risk and nightmares in children. Conclusions: These molecular genetic results support recent findings from twin analysis that show genetic overlap between sleep disturbances and psychotic-like experiences. They also show, to our knowledge for the first time, a genetic correlation between schizophrenia liability and risk of nightmares in childhood.

Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa.

Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness1, affecting 0.9-4% of women and 0.3% of men2-4, with twin-based heritability estimates of 50-60%5. Mortality rates are higher than those in other psychiatric disorders6, and outcomes are unacceptably poor7. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.

Identifying Critical Points of Trajectories of Depressive Symptoms from Childhood to Young Adulthood.

Depression is a common mental illness and research has focused on late childhood and adolescence in an attempt to prevent or reduce later psychopathology and/or social impairments. It is important to establish and study population-averaged trajectories of depressive symptoms across adolescence as this could characterise specific changes in populations and help identify critical points to intervene with treatment. Multilevel growth-curve models were used to explore adolescent trajectories of depressive symptoms in 9301 individuals (57% female) from the Avon Longitudinal Study of Parents and Children, a UK based pregnancy cohort. Trajectories of depressive symptoms were constructed for males and females using the short mood and feelings questionnaire over 8 occasions, between 10 and 22 years old. Critical points of development such as age of peak velocity for depressive symptoms (the age at which depressive symptoms increase most rapidly) and the age of maximum depressive symptoms were also derived. The results suggested that from similar initial levels of depressive symptoms at age 11, females on average experienced steeper increases in depressive symptoms than males over their teenage and adolescent years until around the age of 20 when levels of depressive symptoms plateaued and started to decrease for both sexes. Females on average also had an earlier age of peak velocity of depressive symptoms that occurred at 13.5 years, compared to males who on average had an age of peak velocity at 16 years old. Evidence was less clear for a difference between the ages of maximum depressive symptoms which were on average 19.6 years for females and 20.4 for males. Identifying critical periods for different population subgroups may provide useful knowledge for treating and preventing depression and could be tailored to be time specific for certain groups. Possible explanations and recommendations are discussed.

Evaluation of the causal effects between subjective wellbeing and cardiometabolic health: mendelian randomisation study.

OBJECTIVES: To investigate whether the association between subjective wellbeing (subjective happiness and life satisfaction) and cardiometabolic health is causal. DESIGN: Two sample, bidirectional mendelian randomisation study. SETTING: Genetic data taken from various cohorts comprised of the general population (mostly individuals of European ancestry, plus a small proportion of other ancestries); follow-up analysis included individuals from the United Kingdom. PARTICIPANTS: Summary data were used from previous genome wide association studies (number of participants ranging from 83 198 to 339 224), which investigated traits related to cardiovascular or metabolic health, had the largest sample sizes, and consisted of the most similar populations while minimising sample overlap. A follow-up analysis included 337 112 individuals from the UK Biobank (54% female (n=181 363), mean age 56.87 years (standard deviation 8.00) at recruitment). MAIN OUTCOME MEASURES: Subjective wellbeing and 11 measures of cardiometabolic health (coronary artery disease; myocardial infarction; total, high density lipoprotein, and low density lipoprotein cholesterol; diastolic and systolic blood pressure; body fat; waist to hip ratio; waist circumference; and body mass index). RESULTS: Evidence of a causal effect of body mass index on subjective wellbeing was seen; each 1 kg/m2 increase in body mass index caused a -0.045 (95% confidence interval -0.084 to -0.006, P=0.02) standard deviation reduction in subjective wellbeing. Follow-up analysis of this association in an independent sample from the UK Biobank provided strong evidence of an effect of body mass index on satisfaction with health (ß=-0.035 unit decrease in health satisfaction (95% confidence interval -0.043 to -0.027) per standard deviation increase in body mass index, P<0.001). No clear evidence of a causal effect was seen between subjective wellbeing and the other cardiometabolic health measures, in either direction. CONCLUSIONS: These results suggest that a higher body mass index is associated with a lower subjective wellbeing. A follow-up analysis confirmed this finding, suggesting that the effect in middle aged people could be driven by satisfaction with health. Body mass index is a modifiable determinant, and therefore, this study provides further motivation to tackle the obesity epidemic because of the knock-on effects of higher body mass index on subjective wellbeing.

Moderators of wellbeing interventions: Why do some people respond more positively than others?

Interventions rarely have a universal effect on all individuals. Reasons ranging from participant characteristics, context and fidelity of intervention completion could cause some people to respond more positively than others. Understanding these individual differences in intervention response may provide clues to the mechanisms behind the intervention, as well as inform future designs to make interventions maximally beneficial for all. Here we focus on an intervention designed to improve adolescent wellbeing, and explore potential moderators using a representative and well-powered sample. 16-year old participants (N = 932) in the Twins Wellbeing Intervention Study logged online once a week to complete control and wellbeing-enhancing activities consecutively. Throughout the study participants also provided information about a range of potential moderators of intervention response including demographics, seasonality, personality, baseline characteristics, activity fit, and effort. As expected, some individuals gained more from the intervention than others; we used multi-level modelling to test for moderation effects that could explain these individual differences. Of the 15 moderators tested, none significantly explained individual differences in intervention response in the intervention and follow-up phases. Self-reported effort and baseline positive affect had a notable effect in moderating response in the control phase, during which there was no overall improvement in wellbeing and mental health. Our results did not replicate the moderation effects that have been suggested by previous literature and future work needs to reconcile these differences. They also show that factors that have previously been shown to influence baseline wellbeing do not also influence an individual's ability to benefit from a wellbeing intervention. Although future research should continue to explore potential moderators of intervention efficacy, our results suggest that the beneficial effect of positive activities in adolescents were universal across such factors as sex and socioeconomic status, bolstering claims of the scalability of positive activities to increase adolescent wellbeing.

Social support and mental health in late adolescence are correlated for genetic, as well as environmental, reasons.

Late adolescence is a crucial, but underexplored, developmental stage with respect to the aetiology of social support. These individuals are experiencing many major life changes and social support can help them adjust to the associated environmental stressors of this time. Using 1,215 18-year-old twin pairs from the Twins Early Development Study, we collected measures of two indices of support: support quality and support quantity, as well as wellbeing and depression. Both support indices were moderately heritable (55% and 49%, respectively), an interesting finding given the many environmental changes that late adolescents are encountering that could be environmentally altering their social network structures. Finding a genetic influence on support suggests the presence of gene-environment correlation whereby individuals create and perceive their supportive environment based upon their genetic predispositions. Shared genetic influences mediated the moderate phenotypic correlation (mean r = 0.46) between support and mental health. Genetic correlations were higher between support quality and mental health (mean rA = 0.75), than between support quantity and mental health (mean rA = 0.54), reflecting the phenotypic pattern. This suggests that interventions should focus more on making late adolescents aware of the support quality around them than encouraging them to increase their social network size.

Genetic and environmental correlations between subjective wellbeing and experience of life events in adolescence.

Some life events appear heritable due to the genetic influence on related behaviours. Shared genetic influence between negative behaviours and negative life events has previously been established. This study investigated whether subjective wellbeing and positive life events were genetically associated. Participants in the Twins Early Development Study (aged 16.32 ± .68 years) completed subjective wellbeing and life events assessments via two separate studies (overlapping N for wellbeing and life events measures ranged from 3527 to 9350). We conducted bivariate twin models between both positive and negative life events with subjective wellbeing and related positive psychological traits including subjective happiness, life satisfaction, optimism, hopefulness and gratitude measured at 16 years. Results suggested that the heritability of life events can partially be explained by shared genetic influences with the wellbeing indicators. Wellbeing traits were positively genetically correlated with positive life events and negatively correlated with negative life events (except curiosity where there was no correlation). Those positive traits that drive behaviour (grit and ambition) showed the highest genetic correlation with life events, whereas the reflective trait gratitude was less correlated. This suggests that gene-environment correlations might explain the observed genetic association between life events and wellbeing. Inheriting propensity for positive traits might cause you to seek environments that lead to positive life events and avoid environments which make negative life events more likely.

Personalized Media: A Genetically Informative Investigation of Individual Differences in Online Media Use.

Online media use has become an increasingly important behavioral domain over the past decade. However, studies into the etiology of individual differences in media use have focused primarily on pathological use. Here, for the first time, we test the genetic influences on online media use in a UK representative sample of 16 year old twins, who were assessed on time spent on educational (N = 2,585 twin pairs) and entertainment websites (N = 2,614 twin pairs), time spent gaming online (N = 2,635 twin pairs), and Facebook use (N = 4,333 twin pairs). Heritability was substantial for all forms of online media use, ranging from 34% for educational sites to 37% for entertainment sites and 39% for gaming. Furthermore, genetics accounted for 24% of the variance in Facebook use. Our results support an active model of the environment, where young people choose their online engagements in line with their genetic propensities.

Exploring the Genetic Etiology of Trust in Adolescents: Combined Twin and DNA Analyses.

Behavioral traits generally show moderate to strong genetic influence, with heritability estimates of around 50%. Some recent research has suggested that trust may be an exception because it is more strongly influenced by social interactions. In a sample of over 7,000 adolescent twins from the United Kingdom's Twins Early Development Study, we found broad sense heritability estimates of 57% for generalized trust and 51% for trust in friends. Genomic-relatedness-matrix restricted maximum likelihood (GREML) estimates in the same sample indicate that 21% of the narrow sense genetic variance can be explained by common single nucleotide polymorphisms for generalized trust and 43% for trust in friends. As expected, this implies a large amount of unexplained heritability, although power is low for estimating DNA-based heritability. The missing heritability may be accounted for by interactions between DNA and the social environment during development or via gene-environment correlations with rare variants. How these genes and environments correlate seem especially important for the development of trust.