Practitioner review: A critical perspective on gene-environment interaction models--what impact should they have on clinical perceptions and practice?

Tradeoffs in Modeling Context Dependency in Complex Trait Genetics

Genetic effects on complex traits may depend on context, such as age, sex, environmental exposures or social settings. However, it is often unclear if the extent of context dependency, or Gene-by-Environment interaction (GxE), merits more involved models than the additive model typically used to analyze data from genome-wide association studies (GWAS). Here, we suggest considering the utility of GxE models in GWAS as a tradeoff between bias and variance parameters. In particular, We derive a decision rule for choosing between competing models for the estimation of allelic effects. The rule weighs the increased estimation noise when context is considered against the potential bias when context dependency is ignored. In the empirical example of GxSex in human physiology, the increased noise of context-specific estimation often outweighs the bias reduction, rendering GxE models less useful when variants are considered independently. However, we argue that for complex traits, the joint consideration of context dependency across many variants mitigates both noise and bias. As a result, polygenic GxE models can improve both estimation and trait prediction. Finally, we exemplify (using GxDiet effects on longevity in fruit flies) how analyses based on independently ascertained "top hits" alone can be misleading, and that considering polygenic patterns of GxE can improve interpretation.

Genotype-Environment Interaction in ADHD: Genetic Predisposition Determines the Extent to Which Environmental Influences Explain Variability in the Symptom Dimensions Hyperactivity and Inattention

Although earlier research has shown that individual differences on the spectrum of attention deficit hyperactivity disorder (ADHD) are highly heritable, emerging evidence suggests that symptoms are associated with complex interactions between genes and environmental influences. This study investigated whether a genetic predisposition [Note that the term 'genetic predisposition' was used in this manuscript to refer to an estimate based on twin modeling (an individual's score on the latent trait that resembles additive genetic influences) in the particular population being examined.] for the symptom dimensions hyperactivity and inattention determines the extent to which unique-environmental influences explain variability in these symptoms. To this purpose, we analysed a sample drawn from the Twins Early Development Study (TEDS) that consisted of item-level scores of 2168 16-year-old twin pairs who completed both the Strengths and Difficulties Questionnaire (SDQ; Goodman, in J Child Psychol Psychiatry 38:581-586, 1997) and the Strength and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN; Swanson, in Paper presented at the meeting of the American Psychological Association, Los Angeles, 1981) questionnaire. To maximize the psychometric information to measure ADHD symptoms, psychometric analyses were performed to investigate whether the items from the two questionnaires could be combined to form two longer subscales. In the estimation of genotype-environment interaction, we corrected for error variance heterogeneity in the measurement of ADHD symptoms through the application of item response theory (IRT) measurement models. A positive interaction was found for both hyperactivity (e.g., [Formula: see text] = 2.20 with 95% highest posterior density interval equal to [1.79;2.65] and effect size equal to 3.00) and inattention (e.g., [Formula: see text] = 2.16 with 95% highest posterior density interval equal to [1.56;2.79] and effect size equal to 3.07). These results indicate that unique-environmental influences were more important in creating individual differences in both hyperactivity and inattention for twins with a genetic predisposition for these symptoms than for twins without such a predisposition.

Parenting in the Context of the Child: Genetic and Social Processes

The focus on the role of parenting in child development has a long-standing history. When measures of parenting precede changes in child development, researchers typically infer a causal role of parenting practices and attitudes on child development. However, this research is usually conducted with parents raising their own biological offspring. Such research designs cannot account for the effects of genes that are common to parents and children, nor for genetically influenced traits in children that influence how they are parented and how parenting affects them. The aim of this monograph is to provide a clearer view of parenting by synthesizing findings from the Early Growth and Development Study (EGDS). EGDS is a longitudinal study of adopted children, their birth parents, and their rearing parents studied across infancy and childhood. Families (N = 561) were recruited in the United States through adoption agencies between 2000 and 2010. Data collection began when adoptees were 9 months old (males = 57.2%; White 54.5%, Black 13.2%, Hispanic/Latinx 13.4%, Multiracial 17.8%, other 1.1%). The median child age at adoption placement was 2 days (M = 5.58, SD = 11.32). Adoptive parents were predominantly in their 30s, White, and coming from upper-middle- or upper-class backgrounds with high educational attainment (a mode at 4-year college or graduate degree). Most adoptive parents were heterosexual couples, and were married at the beginning of the project. The birth parent sample was more racially and ethnically diverse, but the majority (70%) were White. At the beginning of the study, most birth mothers and fathers were in their 20s, with a mode of educational attainment at high school degree, and few of them were married. We have been following these family members over time, assessing their genetic influences, prenatal environment, rearing environment, and child development. Controlling for effects of genes common to parents and children, we confirmed some previously reported associations between parenting, parent psychopathology, and marital adjustment in relation to child problematic and prosocial behavior. We also observed effects of children's heritable characteristics, characteristics thought to be transmitted from parent to child by genetic means, on their parents and how those effects contributed to subsequent child development. For example, we found that genetically influenced child impulsivity and social withdrawal both elicited harsh parenting, whereas a genetically influenced sunny disposition elicited parental warmth. We found numerous instances of children's genetically influenced characteristics that enhanced positive parental influences on child development or that protected them from harsh parenting. Integrating our findings, we propose a new, genetically informed process model of parenting. We posit that parents implicitly or explicitly detect genetically influenced liabilities and assets in their children. We also suggest future research into factors such as marital adjustment, that favor parents responding with appropriate protection or enhancement. Our findings illustrate a productive use of genetic information in prevention research: helping parents respond effectively to a profile of child strengths and challenges rather than using genetic information simply to identify some children unresponsive to current preventive interventions.

The levels problem in psychopathology

Psychiatric disorders are studied at multiple levels, but there is no agreement on how these levels are related to each other, or how they should be understood in the first place. In this paper, I provide an account of levels and their relationships that is suited for psychopathology, drawing from recent debates in philosophy of science. Instead of metaphysical issues, the focus is on delivering an understanding of levels that is relevant and useful for scientific practice. I also defend a pragmatic approach to the question of reduction, arguing that even in-principle reductionists should embrace pluralism in practice. Finally, I discuss the benefits and challenges in integrating explanations and models of different levels.

Messaging in Biological Psychiatry: Misrepresentations, Their Causes, and Potential Consequences

Most experts in the field of psychiatry recognize that neuroscience advances have yet to be translated into clinical practice. The main message delivered to laypeople, however, is that mental disorders are brain diseases cured by scientifically designed medications. Here we describe how this misleading message is generated. We summarize the academic studies describing how biomedical observations are often misrepresented in the scientific literature through various forms of data embellishment, publication biases favoring initial and positive studies, improper interpretations, and exaggerated conclusions. These misrepresentations also affect biological psychiatry and are spread through mass media documents. Exacerbated competition, hyperspecialization, and the need to obtain funding for research projects might drive scientists to misrepresent their findings. Moreover, journalists are unaware that initial studies, even when positive and promising, are inherently uncertain. Journalists preferentially cover them and almost never inform the public when those studies are disconfirmed by subsequent research. This explains why reductionist theories about mental health often persist in mass media even though the scientific claims that have been put forward to support them have long been contradicted. These misrepresentations affect the care of patients. Indeed, studies show that a neuro-essentialist conceptualization of mental disorders negatively affects several aspects of stigmatization, reduces the chances of patients' healing, and overshadows psychotherapeutic and social approaches that have been found effective in alleviating mental suffering. Public information about mental health should avoid these reporting biases and give equal consideration to the biological, psychological, and social aspects of mental health.

No Support for Historical Candidate Gene or Candidate Gene-by-Interaction Hypotheses for Major Depression Across Multiple Large Samples

OBJECTIVE

Interest in candidate gene and candidate gene-by-environment interaction hypotheses regarding major depressive disorder remains strong despite controversy surrounding the validity of previous findings. In response to this controversy, the present investigation empirically identified 18 candidate genes for depression that have been studied 10 or more times and examined evidence for their relevance to depression phenotypes.

METHODS

Utilizing data from large population-based and case-control samples (Ns ranging from 62,138 to 443,264 across subsamples), the authors conducted a series of preregistered analyses examining candidate gene polymorphism main effects, polymorphism-by-environment interactions, and gene-level effects across a number of operational definitions of depression (e.g., lifetime diagnosis, current severity, episode recurrence) and environmental moderators (e.g., sexual or physical abuse during childhood, socioeconomic adversity).

RESULTS

No clear evidence was found for any candidate gene polymorphism associations with depression phenotypes or any polymorphism-by-environment moderator effects. As a set, depression candidate genes were no more associated with depression phenotypes than noncandidate genes. The authors demonstrate that phenotypic measurement error is unlikely to account for these null findings.

CONCLUSIONS

The study results do not support previous depression candidate gene findings, in which large genetic effects are frequently reported in samples orders of magnitude smaller than those examined here. Instead, the results suggest that early hypotheses about depression candidate genes were incorrect and that the large number of associations reported in the depression candidate gene literature are likely to be false positives.

Implicit associations to infant cry: Genetics and early care experiences influence caregiving propensities

Adults' sensitive appraisal of and response to infant cry play a foundational role in child development. Employing a gene × environment (G × E) approach, this study investigated the interaction of genetic polymorphisms of the serotonin transporter gene (5-HTTLPR) and oxytocin receptor genes (OXTR; rs53576, rs2254298) with early parental care experiences in influencing adults' implicit associations to infant cry. Eighty nulliparous adults (40 females, 40 males) responded to the Parental Acceptance-Rejection Questionnaire (PARQ), a measure of early care experiences, and participated in a Single Category Implicit Association Task (SC-IAT) to measure implicit associations to infant cry. Independent of parental experience, the valence of the implicit response to infant cry is associated with the serotonin transporter gene polymorphism (5-HTTLPR), with LL-carriers showing more positive implicit associations than S-carriers. OXTR rs53576 moderated the relation between parental rejection and implicit appraisal of infant cry: A-carriers who experienced negative early care showed an implicit positive appraisal of infant cry, whereas in GG carriers, positive early care experiences were associated with an implicit positive reaction to infant cry. OXTR rs2254298 had no relation to implicit associations to infant cry or to early care experiences. These findings cast light on the possible interplay of genetic inheritance and early environment in influencing adults' responses to infant cry that may be incorporated into screening protocols aimed at identifying at-risk adult-infant interactions.

Somatic comorbidity in children and adolescents with psychiatric disorders

In the adult population, psychiatric disorders are associated with somatic illness. Explanatory life style factors have been found, but also a failure to recognize somatic illness in this group. Another factor is side effects from long-term use of antipsychotic drugs. Given the psychiatric-somatic comorbidity in the adult population, it is of interest to investigate whether an association exists already during childhood. The aim of the present study was to investigate the frequency of somatic illness in children and adolescents with a psychiatric diagnose. Data were obtained from the regional health care database Vega, Sweden. Psychiatric and somatic diagnoses obtained during 2011-2013 for individuals aged 3-18 years were extracted. Descriptive statistics were used to examine difference in somatic morbidity between children with and without psychiatric diagnoses. Logistic regression was used in age-stratified models to test the association between psychiatric and somatic diagnoses. Anxiety and behavioral disorders were associated with all somatic conditions investigated at nearly all ages. The same applied to substance use, investigated at age 9-18 years. Affective disorders were associated with all somatic conditions at age 12-18 years. Psychotic conditions were associated with asthma, bowel disorders and myalgia in adolescents. Children with psychiatric disorders are at remarkably high risk for concurrent somatic illness. The associations span across many types of conditions and across all ages. The results support the need for awareness of somatic morbidity in child and adolescent psychiatric clinical settings, and the need for coordinated health care for children with comorbid states.

Application of Research Domain Criteria to childhood and adolescent impulsive and addictive disorders: Implications for treatment

The Research Domain Criteria (RDoC) initiative provides a large-scale, dimensional framework for the integration of research findings across traditional diagnoses, with the long-term aim of improving existing psychiatric treatments. A neurodevelopmental perspective is essential to this endeavor. However, few papers synthesizing research findings across childhood and adolescent disorders exist. Here, we discuss how the RDoC framework may be applied to the study of childhood and adolescent impulsive and addictive disorders in order to improve neurodevelopmental understanding and to enhance treatment development. Given the large scope of RDoC, we focus on a single construct highly relevant to addictive and impulsive disorders - initial responsiveness to reward attainment. Findings from genetic, molecular, neuroimaging and other translational research methodologies are highlighted.

[Prediction of binge drinking in young adults: a cohort study over nine years]

Prediction of binge drinking in young adults: a cohort study over nine years Abstract.

OBJECTIVE

Which person characteristics and environmental factors predict binge drinking at age 21?

METHOD

A longitudinal observational study with a nine-year follow-up. A total of 5,176 adolescents from the German states Schleswig-Holstein and Saxony-Anhalt were surveyed in 2006 with paper-pencil questionnaires (mean age 12.6 years, SD = 0.6). A follow-up assessment was conducted in the year 2015. Baseline predictors were age, gender, school type, school performance, parenting style, early experience with alcohol, alcohol use of parents, alcohol use of friends, and sensation seeking. Primary outcome in 2015 was binge drinking at least once a month (six or more alcoholic drinks during one drinking occasion).

RESULTS

A subsample of 1,087 (20.9 %) of the former students could be surveyed nine years after baseline (mean age 21.6 years, SD = 0.8). One out of four (25.4 %) reported binge drinking at least once in a month. A multiple regression model revealed three significant predictors of binge drinking: male gender, early experience with alcohol and frequency of parental alcohol use at baseline.

CONCLUSIONS

Perceived frequency of parental alcohol use might be an important risk factor for children's alcohol use in early adulthood. Parents need to reflect their role as alcohol-specific socialization agents.

Personality as an intermediate phenotype for genetic dissection of alcohol use disorder

Genetic and environmental interactive influences on predisposition to develop alcohol use disorder (AUD) account for the high heterogeneity among AUD patients and make research on the risk and resiliency factors complicated. Several attempts have been made to identify the genetic basis of AUD; however, only few genetic polymorphisms have consistently been associated with AUD. Intermediate phenotypes are expected to be in-between proxies of basic neuronal biological processes and nosological symptoms of AUD. Personality is likely to be a top candidate intermediate phenotype for the dissection of the genetic underpinnings of different subtypes of AUD. To date, 38 studies have investigated personality traits, commonly assessed by the Cloninger's Tridimensional Personality Questionnaire (TPQ) or Temperament and Character Inventory (TCI), in relation to polymorphisms of candidate genes of neurotransmitter systems in alcohol-dependent patients. Particular attention has been given to the functional polymorphism of the serotonin transporter gene (5-HTTLPR), however, leading to contradictory results, whereas results with polymorphisms in other candidate monoaminergic genes (e.g., tryptophan hydroxylase, serotonin receptors, monoamine oxidases, dopamine receptors and transporter) are sparse. Only one genome-wide association study has been performed so far and identified the ABLIM1 gene of relevance for novelty seeking, harm avoidance and reward dependence in alcohol-dependent patients. Studies investigating genetic factors together with personality could help to define more homogenous subgroups of AUD patients and facilitate treatment strategies. This review also urges the scientific community to combine genetic data with psychobiological and environmental data to further dissect the link between personality and AUD.

The CogBIAS longitudinal study protocol: cognitive and genetic factors influencing psychological functioning in adolescence

BACKGROUND

Optimal psychological development is dependent upon a complex interplay between individual and situational factors. Investigating the development of these factors in adolescence will help to improve understanding of emotional vulnerability and resilience. The CogBIAS longitudinal study (CogBIAS-L-S) aims to combine cognitive and genetic approaches to investigate risk and protective factors associated with the development of mood and impulsivity-related outcomes in an adolescent sample.

METHODS

CogBIAS-L-S is a three-wave longitudinal study of typically developing adolescents conducted over 4 years, with data collection at age 12, 14 and 16. At each wave participants will undergo multiple assessments including a range of selective cognitive processing tasks (e.g. attention bias, interpretation bias, memory bias) and psychological self-report measures (e.g. anxiety, depression, resilience). Saliva samples will also be collected at the baseline assessment for genetic analyses. Multilevel statistical analyses will be performed to investigate the developmental trajectory of cognitive biases on psychological functioning, as well as the influence of genetic moderation on these relationships.

DISCUSSION

CogBIAS-L-S represents the first longitudinal study to assess multiple cognitive biases across adolescent development and the largest study of its kind to collect genetic data. It therefore provides a unique opportunity to understand how genes and the environment influence the development and maintenance of cognitive biases and provide insight into risk and protective factors that may be key targets for intervention.

What is the biological reality of gene-environment interaction estimates? An assessment of bias in developmental models

BACKGROUND

Standard models used to test gene-environment interaction (G × E) hypotheses make the causal assumption that there are no unobserved variables that could be biasing the interaction estimate. Whether this assumption can be met in nonexperimental studies is unclear because the interactive biological pathways from genetic polymorphisms and environments to behavior, and the confounders that can be introduced along these pathways, are often not delineated. This is problematic in the context of studies focused on caregiver-child dyads, in which common genes and environments induce gene-environment correlation. To address the impact of sources of bias in G × E models specifically assessing the interaction between child genotype and caregiver behavior, we provide a causal framework that integrates biological and statistical concepts of G × E, and assess the magnitude of bias introduced by various confounding pathways in different causal circumstances.

METHODS

A simulation assessed the magnitude of bias introduced by four types of confounding pathways in different causal models. Unadjusted and adjusted statistical models were then applied to the simulated data to assess the efficacy of these procedures to capture unbiased G × E estimates. Finally, the simulation was run under null effects of the genotype to assess the impact of biasing sources on the false-positive rate.

RESULTS

Common environmental pathways between caregiver and child inflated G × E estimates and raised the false-positive rate. Evocative effects of the child also inflated G × E estimates.

CONCLUSIONS

Gene-environment interaction studies should be approached with consideration to the causal pathways at play and the confounding opportunities along these pathways to facilitate the inclusion of adequate statistical controls and correct inferences from study findings. Bridging biological and statistical concepts of G × E can significantly improve research design and the communication of how a G × E process fits into a broader developmental framework.

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.

Teacher-student relationships and adolescent behavioral engagement and rule-breaking behavior: The moderating role of dopaminergic genes

This study examined whether the dopamine transporter DAT1 and the dopamine receptor DRD4 genes moderate the effect of student-reported teacher-student relationship affiliation or dissatisfaction on parent-reported adolescent rule-breaking behavior and behavioral engagement. The sample included 1053 adolescents (51% boys, Mage=13.79) from grades 7 to 9. Regression analyses were conducted using Mplus while controlling for multiple testing and nested data. Adolescents who experienced stronger affiliation with their teachers were more engaged in school, whereas greater dissatisfaction predicted more rule-breaking behavior. In addition, a significant gene-environment interaction was found for both genes examined. The link between low teacher-student affiliation and low engagement was more pronounced for DAT1-10R homozygotes. The link between high teacher-student dissatisfaction and more rule-breaking was stronger for DRD4 non-long carriers. Implications for understanding the role of teacher-student relationships in adolescence and suggestions for future research are outlined.

Annual Research Review: Discovery science strategies in studies of the pathophysiology of child and adolescent psychiatric disorders--promises and limitations

BACKGROUND

Psychiatric science remains descriptive, with a categorical nosology intended to enhance interobserver reliability. Increased awareness of the mismatch between categorical classifications and the complexity of biological systems drives the search for novel frameworks including discovery science in Big Data. In this review, we provide an overview of incipient approaches, primarily focused on classically categorical diagnoses such as schizophrenia (SZ), autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD), but also reference convincing, if focal, advances in cancer biology, to describe the challenges of Big Data and discovery science, and outline approaches being formulated to overcome existing obstacles.

FINDINGS

A paradigm shift from categorical diagnoses to a domain/structure-based nosology and from linear causal chains to complex causal network models of brain-behavior relationship is ongoing. This (r)evolution involves appreciating the complexity, dimensionality, and heterogeneity of neuropsychiatric data collected from multiple sources ('broad' data) along with data obtained at multiple levels of analysis, ranging from genes to molecules, cells, circuits, and behaviors ('deep' data). Both of these types of Big Data landscapes require the use and development of robust and powerful informatics and statistical approaches. Thus, we describe Big Data analysis pipelines and the promise and potential limitations in using Big Data approaches to study psychiatric disorders.

CONCLUSIONS

We highlight key resources available for psychopathological studies and call for the application and development of Big Data approaches to dissect the causes and mechanisms of neuropsychiatric disorders and identify corresponding biomarkers for early diagnosis.

Gene-Stress-Epigenetic Regulation of FKBP5: Clinical and Translational Implications

Stress responses and related outcomes vary markedly across individuals. Elucidating the molecular underpinnings of this variability is of great relevance for developing individualized prevention strategies and treatments for stress-related disorders. An important modulator of stress responses is the FK506-binding protein 51 (FKBP5/FKBP51). FKBP5 acts as a co-chaperone that modulates not only glucocorticoid receptor activity in response to stressors but also a multitude of other cellular processes in both the brain and periphery. Notably, the FKBP5 gene is regulated via complex interactions among environmental stressors, FKBP5 genetic variants, and epigenetic modifications of glucocorticoid-responsive genomic sites. These interactions can result in FKBP5 disinhibition that has been shown to contribute to a number of aberrant phenotypes in both rodents and humans. Consequently, FKBP5 blockade may hold promise as treatment intervention for stress-related disorders, and recently developed selective FKBP5 blockers show encouraging results in vitro and in rodent models. Although risk for stress-related disorders is conferred by multiple environmental and genetic factors, the findings related to FKBP5 illustrate how a deeper understanding of the molecular and systemic mechanisms underlying specific gene-environment interactions may provide insights into the pathogenesis of stress-related disorders.

Psychiatric symptoms in adolescents: FKBP5 genotype--early life adversity interaction effects

Psychiatric disorders are multi-factorial and their symptoms overlap. Constitutional and environmental factors influence each other, and this contributes to risk and resilience in mental ill-health. We investigated functional genetic variation of stress responsiveness, assessed as FKBP5 genotype, in relation to early life adversity and mental health in two samples of adolescents. One population-based sample of 909 12-year-old adolescents was assessed using the Life Incidence of Traumatic Events scale and the Strengths and Difficulties Questionnaire. One sample of 398 17-year-old adolescents, enriched for poly-victimized individuals (USSS), was assessed using the Juvenile Victimization Questionnaire and the Trauma Symptom Checklist for Children (TSCC). The FKBP5 rs1360780 and rs3800373 polymorphisms were genotyped using a fluorescence-based competitive allele-specific PCR. Most prominently among poly-victimized older male adolescents, the least common alleles of the polymorphisms, in interaction with adverse life events, were associated with psychiatric symptoms, after controlling for ethno-socio-economic factors. The interaction effect between rs3800373 and adverse life events on the TSCC sub-scales-anxiety, depression, anger, and dissociation-and with the rs1360780 on dissociation in the USSS cohort remained significant after Bonferroni correction. This pattern of association is in line with the findings of clinical and neuroimaging studies, and implies interactive effects of FKBP5 polymorphisms and early life environment on several psychiatric symptoms. These correlates add up to provide constructs that are relevant to several psychiatric symptoms, and to identify early predictors of mental ill-health.

Genes, environments and depressions in young people

Among the common mental illnesses in childhood and adolescence, the unipolar depressions are the most concerning. These mental illnesses are aetiologically and clinically heterogeneous and little is known about their pathophysiology. This selected review considers the contribution of genetic and environmental factors in the emergence of these illnesses in the second decade of life.

Epigenetics of Stress-Related Psychiatric Disorders and Gene × Environment Interactions

A deeper understanding of the pathomechanisms leading to stress-related psychiatric disorders is important for the development of more efficient preventive and therapeutic strategies. Epidemiological studies indicate a combined contribution of genetic and environmental factors in the risk for disease. The environment, particularly early life severe stress or trauma, can lead to lifelong molecular changes in the form of epigenetic modifications that can set the organism off on trajectories to health or disease. Epigenetic modifications are capable of shaping and storing the molecular response of a cell to its environment as a function of genetic predisposition. This provides a potential mechanism for gene-environment interactions. Here, we review epigenetic mechanisms associated with the response to stress and trauma exposure and the development of stress-related psychiatric disorders. We also look at how they may contribute to our understanding of the combined effects of genetic and environmental factors in shaping disease risk.

Adolescent Loneliness and the Interaction between the Serotonin Transporter Gene (5-HTTLPR) and Parental Support: A Replication Study

Gene-by-environment interaction (GxEs) studies have gained popularity over the last decade, but the robustness of such observed interactions has been questioned. The current study contributes to this debate by replicating the only study on the interaction between the serotonin transporter gene (5-HTTLPR) and perceived parental support on adolescents’ peer-related loneliness. A total of 1,111 adolescents (51% boys) with an average age of 13.70 years (SD = 0.93) participated and three annual waves of data were collected. At baseline, adolescent-reported parental support and peer-related loneliness were assessed and genetic information was collected. Assessment of peer-related loneliness was repeated at Waves 2 and 3. Using a cohort-sequential design, a Latent Growth Curve Model was estimated. Overall, a slight increase of loneliness over time was found. However, the development of loneliness over time was found to be different for boys and girls: girls’ levels of loneliness increased over time, whereas boys’ levels of loneliness decreased. Parental support was inversely related to baseline levels of loneliness, but unrelated to change of loneliness over time. We were unable to replicate the main effect of 5-HTTLPR or the 5-HTTLPR x Support interaction effect. In the Discussion, we examine the implications of our non-replication.

Kernel Approach for Modeling Interaction Effects in Genetic Association Studies of Complex Quantitative Traits

The etiology of complex traits likely involves the effects of genetic and environmental factors, along with complicated interaction effects between them. Consequently, there has been interest in applying genetic association tests of complex traits that account for potential modification of the genetic effect in the presence of an environmental factor. One can perform such an analysis using a joint test of gene and gene-environment interaction. An optimal joint test would be one that remains powerful under a variety of models ranging from those of strong gene-environment interaction effect to those of little or no gene-environment interaction effect. To fill this demand, we have extended a kernel machine based approach for association mapping of multiple SNPs to consider joint tests of gene and gene-environment interaction. The kernel-based approach for joint testing is promising, because it incorporates linkage disequilibrium information from multiple SNPs simultaneously in analysis and permits flexible modeling of interaction effects. Using simulated data, we show that our kernel machine approach typically outperforms the traditional joint test under strong gene-environment interaction models and further outperforms the traditional main-effect association test under models of weak or no gene-environment interaction effects. We illustrate our test using genome-wide association data from the Grady Trauma Project, a cohort of highly traumatized, at-risk individuals, which has previously been investigated for interaction effects.

The hidden efficacy of interventions: gene×environment experiments from a differential susceptibility perspective

The efficacy of interventions might be underestimated or even go undetected as a main effect when it is hidden in gene-by-environment (G×E) interactions. This review moves beyond the problems thwarting correlational G×E research to propose genetic differential susceptibility experiments. G×E experiments can test the bright side as well as the dark side of the moderating role of genotypes traditionally considered to represent vulnerability to negative conditions. The differential susceptibility model predicts that carriers of these risk genotypes profit most from interventions changing the environment for the better. The evolutionary background of G×E and differential susceptibility is discussed, and statistical methods for the analysis of differential susceptibility (versus diathesis stress) are reviewed. Then, based on results from 22 randomized G×E experiments, meta-analytic evidence for the differential susceptibility model is presented. Intervention effects are much stronger in the susceptible genotypes than in the nonsusceptible genotypes. The final sections suggest possibilities to broaden the G component in the G×E equation by including genetic pathways, and to broaden the E component by including methylation level and gene expression as promising ways to probe the concept of the environment more deeply and address the perennial issue of what works for whom.