Estimating the heritability of reporting stressful life events captured by common genetic variants

Interplay between polygenic risk for mood disorders and stressful life events in bipolar disorder

BACKGROUND

Although genetic and environmental factors are involved in the aetiology of bipolar disorder [BD], studies focused on their interplay are lacking. The current investigation examines interactions and correlations between polygenic risk scores [PRS] for BD and major depressive disorder [MDD] with stressful life events [SLEs] in liability for BD.

METHODS

This study used data from 1715 participants (862 bipolar cases and 853 controls) taken from UK and Canadian samples. The List of Threatening Experiences Questionnaire recorded SLEs that occurred 6 months before interview for controls and 6 months prior to the first (Canadian sample) and worst (UK sample) depressive and manic episodes for bipolar cases. PRS-BD and PRS-MDD were calculated from the Psychiatric Genomics Consortium.

RESULTS

For the worst depressive episode, the PRS-MDD was significantly correlated with total number of SLEs (β = 0.13, 95 % CI:0.04-0.22, p = 0.003) and dependent SLEs (β = 0.09, 95 % CI:0.02-0.16, p = 0.007). After correction for multiple testing nominally significant correlations were detected for PRS-BD with total number of SLEs (β = 0.11, 95 % CI:0.02-0.20, p = 0.015) and dependent SLEs (β = 0.08, 95 % CI:0.01-0.15, p = 0.019). Among bipolar cases, these associations were slightly stronger but were only of nominal significance for total number of SLEs (PRS-MDD: β = 0.19, 95 % CI:0.04-0.35, p = 0.015; PRS-BD: β = 0.16, 95 % CI:0.01-0.32, p = 0.042) and dependent SLEs (PRS-MDD: β = 0.14, 95 % CI:0.03-0.26, p = 0.015; PRS-BD: β = 0.12, 95 % CI:0.004-0.24, p = 0.043). No other significant gene-environment correlations or interactions were found.

LIMITATIONS

Use of a larger sample size would be beneficial.

CONCLUSIONS

The relationship between SLEs and genetic risk for mood disorders may be best explained through correlations rather than interactions.

Assessing the causal association of trauma with subsequent psychiatric disorders by a Mendelian randomization study trauma and common psychiatric disorders

OBJECTIVE

Trauma has been proposed as a risk factor for the development of psychiatric disorders. This study aimed to determine the causal role of trauma in six common psychiatric disorders.

METHODS

We obtained summary-level data for genetic variants associated with trauma and the corresponding association with psychiatric disorders from previous genome-wide association studies. Two-sample Mendelian randomization analyzes were performed to estimate the causal association between trauma and psychiatric disorders, with inverse variance weighted used as the main method.

RESULTS

Genetically predisposed trauma was associated with an increased risk of psychiatric disorders [odds ratio (OR) =1.24, 95%, confidence interval (CI), 1.09-1.40], anxiety disorder (OR = 1.30, 95% CI, 1.10-1.52) and schizophrenia (OR = 1.48, 95% CI, 1.18-1.84). However, the associations between trauma and sleep disorder (OR = 1.17, 95% CI, 1.01-1.35), as well as depression (OR = 1.09, 95% CI, 1.02-1.16) did not reach a Bonferroni corrected significance level. Besides, no association was observed between trauma and risk of bipolar disorder (OR = 1.21, 95% CI, 0.98-1.48) and eating disorder (OR = 1.28, 95% CI, 0.88-1.86).

CONCLUSION

Trauma might be causally associated with an increased risk of some common psychiatric disorders such as anxiety disorder and schizophrenia. However, little evidence supported an association between trauma and risk of depression, bipolar disorder, sleep disorder, and eating disorder. Our findings offered novel insights into the trauma-mediated development mechanism of psychiatric disorders, and psychological intervention to patients with trauma may be an effective prevention strategy for psychological diseases.

A multivariate genetic analysis of anxiety sensitivity, environmental sensitivity and reported life events in adolescents

BACKGROUND

Despite being considered a measure of environmental risk, reported life events are partly heritable. One mechanism that may contribute to this heritability is genetic influences on sensitivity, relating to how individuals process and interpret internal and external signals. The aim of this study was to explore the genetic and environmental overlap between self-reported life events and measures of sensitivity.

METHODS

At age 17, 2,939 individuals from the Twins Early Development Study (TEDS) completed measures of anxiety sensitivity (Children's Anxiety Sensitivity Index), environmental sensitivity (Highly Sensitive Child Scale) and reported their experience of 20 recent life events. Using multivariate Cholesky decomposition models, we investigated the shared genetic and environmental influences on the associations between these measures of sensitivity and the number of reported life events, as well as both negative and positive ratings of life events.

RESULTS

The majority of the associations between anxiety sensitivity, environmental sensitivity and reported life events were explained by shared genetic influences (60%-75%), with the remainder explained by nonshared environmental influences (25%-40%). Environmental sensitivity showed comparable genetic correlations with both negative and positive ratings of life events (r_A  = .21 and .15), anxiety sensitivity only showed a significant genetic correlation with negative ratings of life events (r_A  = .33). Approximately 10% of the genetic influences on reported life events were accounted for by influences shared with anxiety sensitivity and environmental sensitivity.

CONCLUSION

Differences in how individuals process the contextual aspects of the environment or interpret their own physical and emotional response to environmental stimuli may be one mechanism through which genetic liability influences the subjective experience of life events.

Psychological trauma and the genetic overlap between posttraumatic stress disorder and major depressive disorder

BACKGROUND

Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are commonly reported co-occurring mental health consequences of psychological trauma exposure. The disorders have high genetic overlap. Trauma is a complex phenotype but research suggests that trauma sensitivity has a heritable basis. We investigated whether sensitivity to trauma in those with MDD reflects a similar genetic component in those with PTSD.

METHODS

Genetic correlations between PTSD and MDD in individuals reporting trauma and MDD in individuals not reporting trauma were estimated, as well as with recurrent MDD and single-episode MDD, using genome-wide association study (GWAS) summary statistics. Genetic correlations were replicated using PTSD data from the Psychiatric Genomics Consortium and the Million Veteran Program. Polygenic risk scores were generated in UK Biobank participants who met the criteria for lifetime MDD (N = 29 471). We investigated whether genetic loading for PTSD was associated with reporting trauma in these individuals.

RESULTS

Genetic loading for PTSD was significantly associated with reporting trauma in individuals with MDD [OR 1.04 (95% CI 1.01-1.07), Empirical-p = 0.02]. PTSD was significantly more genetically correlated with recurrent MDD than with MDD in individuals not reporting trauma (rg differences = ~0.2, p < 0.008). Participants who had experienced recurrent MDD reported significantly higher rates of trauma than participants who had experienced single-episode MDD (χ2 > 166, p < 0.001).

CONCLUSIONS

Our findings point towards the existence of genetic variants associated with trauma sensitivity that might be shared between PTSD and MDD, although replication with better powered GWAS is needed. Our findings corroborate previous research highlighting trauma exposure as a key risk factor for recurrent MDD.

Attachment Style Moderates Polygenic Risk for Posttraumatic Stress in United States Military Veterans: Results From the National Health and Resilience in Veterans Study

BACKGROUND

A polygenic risk score (PRS) derived from genome-wide association studies of posttraumatic stress disorder (PTSD) may inform risk for this disorder. To date, however, no known study has examined whether social environmental factors such as attachment style may moderate the relation between PRS and PTSD.

METHODS

We evaluated main and interactive effects of PRS and attachment style on PTSD symptoms in a nationally representative sample of trauma-exposed European-American U.S. military veterans (N = 2030). PRS was derived from a genome-wide association study of PTSD re-experiencing symptoms (N = 146,660) in the Million Veteran Program cohort. Using one-sample Mendelian randomization with data from the UK Biobank (N = 115,099), we evaluated the effects of re-experiencing PRS and attachment style on PTSD symptoms.

RESULTS

Higher re-experiencing PRS and secure attachment style were independently associated with PTSD symptoms. A significant PRS-by-attachment style interaction was also observed (β = -.11, p = .006), with a positive association between re-experiencing PRS and PTSD symptoms observed only among veterans with an insecure attachment style. One-sample Mendelian randomization analyses suggested that the association between PTSD symptoms and attachment style is bidirectional. PRS enrichment analyses revealed a significant interaction between attachment style and a variant mapping to the IGSF11 gene (rs151177743, p = 2.1 × 10^-7), which is implicated in regulating excitatory synaptic transmission and plasticity.

CONCLUSIONS

Attachment style may moderate polygenic risk for PTSD symptoms, and a novel locus implicated in synaptic transmission and plasticity may serve as a possible biological mediator of this association. These findings may help inform interpersonally oriented treatments for PTSD for individuals with high polygenic risk for this disorder.

Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.

Why sleep matters for young people who may get depressed

Depression and anxiety are negative emotional states familiar to us all through personal experience. Less familiar are severe states of depression, in particular, which can actually shorten the lives of sufferers by over a decade. The relationship of these very severe states of illness to the milder cases more common earlier in development is important. Most patients who have suffered from depression will suffer from further episodes during their lifetime, and an early onset may make recurrence more likely. A number of factors increase the risk for depression, including family history, stressful life events, early life experiences, personality (particularly the traits of neuroticism and perfectionism) and mood lability (marked ups and downs). Sleep disturbance may both provoke and/or signal the onset of mood disorder. Sleep is therefore doubly important as a gateway to treatment. Understanding more about how sleep interacts with the established risk factors would allow vulnerable young people to be identified earlier for more effective intervention. Early identification of sleep disorder and depression allows psychological treatments to be used, which are less effective once a full depressive episode and a cascade of neurobiological and psychological effects have occurred.

The relationship between independent and dependent life events and depression symptoms in Sri Lanka: a twin and singleton study

PURPOSE

Life events have been associated with a variety of mental health conditions including depression. There is a scarcity of research in South Asia exploring the aetiology of independent and dependent life events and their relationship with depression symptoms. This study aimed, in a Sri Lankan population, to identify the socio-demographic correlates and genetic and environmental influences on independent and dependent life events and their relationship with depression.

METHODS

Questionnaire data came from the Colombo Twin and Singleton Follow-up Study, CoTaSS-2 (N = 3969), a population study of Sri Lankan twins and singletons. Lifetime-ever independent and dependent life events were measured using a questionnaire and depressive symptoms using the Revised Beck's Depression Inventory. Structural Equation Model-fitting analyses explored the genetic and environmental influences on life events and depression.

RESULTS

Living in a rural environment and financial hardship were associated with greater reporting of independent and dependent life events. Sex differences were evident in the aetiology of life events and depression symptoms. Independent and dependent life events, but not depression symptoms, were heritable in males. Independent life events and depression symptoms, but not dependent life events, were heritable in females. Non-shared environmental influences explained phenotypic associations between independent life events and depression symptoms in both males and females. Genetic and non-shared environmental influences explained the phenotypic associations between dependent life events and depression symptoms in males. Only non-shared environment explained the covariation between dependent life events and depression symptoms in females.

CONCLUSIONS

Socio-demographic correlates of independent and dependent life events were similar to those reported in Western populations. Life events were associated with increased depression symptoms. Contrary to research in Western populations, we found that non-shared environmental, rather than genetic, influences explained much of the covariation between life events and depression symptoms. This suggests that whilst independent LEs may be heritable, the relationship is unlikely to be confounded by genetic influences and has significant implications for possible interventions for depression.

The E Is in the G: Gene-Environment-Trait Correlations and Findings From Genome-Wide Association Studies

Genome-wide association studies (GWASs) have shown that pleiotropy is widespread (i.e., the same genetic variants affect multiple traits) and that complex traits are polygenic (i.e., affected by many genetic variants with very small effect sizes). However, despite the growing number of GWASs, the possible contribution of gene-environment correlations (rGEs) to pleiotropy and polygenicity has been mostly ignored. rGEs can lead to environmentally mediated pleiotropy or gene-environment-trait correlations (rGETs), given that an environment that is affected by one genetically influenced phenotype, can in turn affect a different phenotype. By adding correlations with environmentally mediated genetic variants, rGETs can contribute to polygenicity. Socioeconomic status (SES) and the experience of stressful life events may, for example, be involved in rGETs. Both are genetically influenced and have been associated with a myriad of physical and mental disorders. As a result, GWASs of these disorders may find the genetic correlates of SES and stressful life events. Consequently, some of the genetic correlates of physical and mental disorders may be modified by public policy that affects environments such as SES and stressful life events. Thus, identifying rGETs can shed light on findings from GWASs and have important implications for public health.

Association of Maternal Neurodevelopmental Risk Alleles With Early-Life Exposures

Importance

Early-life exposures, such as prenatal maternal lifestyle, illnesses, nutritional deficiencies, toxin levels, and adverse birth events, have long been considered potential risk factors for neurodevelopmental disorders in offspring. However, maternal genetic factors could be confounding the association between early-life exposures and neurodevelopmental outcomes in offspring, which makes inferring a causal relationship problematic.

Objective

To test whether maternal polygenic risk scores (PRSs) for neurodevelopmental disorders were associated with early-life exposures previously linked to the disorders.

Design, Setting, and Participants

In this UK population-based cohort study, 7921 mothers with genotype data from the Avon Longitudinal Study of Parents and Children (ALSPAC) underwent testing for association of maternal PRS for attention-deficit/hyperactivity disorder (ADHD PRS), autism spectrum disorder (ASD PRS), and schizophrenia (SCZ PRS) with 32 early-life exposures. ALSPAC data collection began September 6, 1990, and is ongoing. Data were analyzed for the current study from April 1 to September 1, 2018.

Exposures

Maternal ADHD PRS, ASD PRS, and SCZ PRS were calculated using discovery effect size estimates from the largest available genome-wide association study and a significance threshold of P < .05.

Main Outcomes and Measures

Outcomes measured included questionnaire data on maternal lifestyle and behavior (eg, smoking, alcohol consumption, body mass index, and maternal age), maternal use of nutritional supplements and medications in pregnancy (eg, acetaminophen, iron, zinc, folic acid, and vitamins), maternal illnesses (eg, diabetes, hypertension, rheumatism, psoriasis, and depression), and perinatal factors (eg, birth weight, preterm birth, and cesarean delivery).

Results

Maternal PRSs were available from 7921 mothers (mean [SD] age, 28.5 [4.8] years). The ADHD PRS was associated with multiple prenatal factors, including infections (odds ratio [OR], 1.11; 95% CI, 1.04-1.18), use of acetaminophen during late pregnancy (OR, 1.11; 95% CI, 1.04-1.18), lower blood levels of mercury (β coefficient, -0.06; 95% CI, -0.11 to -0.02), and higher blood levels of cadmium (β coefficient, 0.07; 95% CI, 0.05-0.09). Little evidence of associations between ASD PRS or SCZ PRS and prenatal factors or of association between any of the PRSs and adverse birth events was found. Sensitivity analyses revealed consistent results.

Conclusions and Relevance

These findings suggest that maternal risk alleles for neurodevelopmental disorders, primarily ADHD, are associated with some pregnancy-related exposures. These findings highlight the need to carefully account for potential genetic confounding and triangulate evidence from different approaches when assessing the effects of prenatal exposures on neurodevelopmental disorders in offspring.

Genome-wide by environment interaction studies of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland

Stress is associated with poorer physical and mental health. To improve our understanding of this link, we performed genome-wide association studies (GWAS) of depressive symptoms and genome-wide by environment interaction studies (GWEIS) of depressive symptoms and stressful life events (SLE) in two UK population-based cohorts (Generation Scotland and UK Biobank). No SNP was individually significant in either GWAS, but gene-based tests identified six genes associated with depressive symptoms in UK Biobank (DCC, ACSS3, DRD2, STAG1, FOXP2 and KYNU; p < 2.77 × 10-6). Two SNPs with genome-wide significant GxE effects were identified by GWEIS in Generation Scotland: rs12789145 (53-kb downstream PIWIL4; p = 4.95 × 10-9; total SLE) and rs17070072 (intronic to ZCCHC2; p = 1.46 × 10-8; dependent SLE). A third locus upstream CYLC2 (rs12000047 and rs12005200, p < 2.00 × 10-8; dependent SLE) when the joint effect of the SNP main and GxE effects was considered. GWEIS gene-based tests identified: MTNR1B with GxE effect with dependent SLE in Generation Scotland; and PHF2 with the joint effect in UK Biobank (p < 2.77 × 10-6). Polygenic risk scores (PRSs) analyses incorporating GxE effects improved the prediction of depressive symptom scores, when using weights derived from either the UK Biobank GWAS of depressive symptoms (p = 0.01) or the PGC GWAS of major depressive disorder (p = 5.91 × 10-3). Using an independent sample, PRS derived using GWEIS GxE effects provided evidence of shared aetiologies between depressive symptoms and schizotypal personality, heart disease and COPD. Further such studies are required and may result in improved treatments for depression and other stress-related conditions.

Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism

Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is associated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism. Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs. Results: Past 6-month life events were positively associated with lifetime MDD status (β=0.21, r ²=1.1%, p=2.5 x 10 ^-25) and neuroticism (β =0.13, r ²=1.9%, p=1.04 x 10 ^-37) at the phenotypic level.  Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10 ^-4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r ²=0.3%, p=3 x 10 ^-5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (r _G=0.33, S.E.=0.08 ) and neuroticism (r _G=0.15, S.E.=0.07). Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.

Genetic and environmental determinants of stressful life events and their overlap with depression and neuroticism

Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is associated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism.

Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs.

Results: Past 6-month life events were positively associated with lifetime MDD status (β=0.21, r ²=1.1%, p=2.5 x 10 ^-25) and neuroticism (β =0.13, r ²=1.9%, p=1.04 x 10 ^-37) at the phenotypic level.  Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10 ^-4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r ²=0.3%, p=3 x 10 ^-5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (r _G=0.33, S.E.=0.08 ) and neuroticism (r _G=0.15, S.E.=0.07).

Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.

Sociogenomics in the 21st Century: An Introduction to the History and Potential of Genetically-informed Social Science

This article reviews research at the intersection of genetics and sociology and provides an introduction to the current data, methods, and theories used in sociogenomic research. To accomplish this, I review behavioral genetics models, candidate gene analysis, genome-wide complex trait analysis, and the use of polygenic scores (sometimes referred to as polygenic risk scores) in the study of complex human behaviors and traits. The information provided is meant to equip readers with the necessary tools to: (1) understand the methodology employed by each type of analysis, (2) intelligently interpret findings from sociogenomic research, and (3) understand the importance of sociologists in the ever-growing field of sociogenomics. To unify these three tasks, I rely on various examples from recent sociogenomic analyses of educational attainment focusing on social stratification and inequality.

Molecular Genetic Analysis Subdivided by Adversity Exposure Suggests Etiologic Heterogeneity in Major Depression

OBJECTIVE

The extent to which major depression is the outcome of a single biological mechanism or represents a final common pathway of multiple disease processes remains uncertain. Genetic approaches can potentially identify etiologic heterogeneity in major depression by classifying patients on the basis of their experience of major adverse events.

METHOD

Data are from the China, Oxford, and VCU Experimental Research on Genetic Epidemiology (CONVERGE) project, a study of Han Chinese women with recurrent major depression aimed at identifying genetic risk factors for major depression in a rigorously ascertained cohort carefully assessed for key environmental risk factors (N=9,599). To detect etiologic heterogeneity, genome-wide association studies, heritability analyses, and gene-by-environment interaction analyses were performed.

RESULTS

Genome-wide association studies stratified by exposure to adversity revealed three novel loci associated with major depression only in study participants with no history of adversity. Significant gene-by-environment interactions were seen between adversity and genotype at all three loci, and 13.2% of major depression liability can be attributed to genome-wide interaction with adversity exposure. The genetic risk in major depression for participants who reported major adverse life events (27%) was partially shared with that in participants who did not (73%; genetic correlation=+0.64). Together with results from simulation studies, these findings suggest etiologic heterogeneity within major depression as a function of environmental exposures.

CONCLUSIONS

The genetic contributions to major depression may differ between women with and those without major adverse life events. These results have implications for the molecular dissection of major depression and other complex psychiatric and biomedical diseases.

Widespread covariation of early environmental exposures and trait-associated polygenic variation

Although gene-environment correlation is recognized and investigated by family studies and recently by SNP-heritability studies, the possibility that genetic effects on traits capture environmental risk factors or protective factors has been neglected by polygenic prediction models. We investigated covariation between trait-associated polygenic variation identified by genome-wide association studies (GWASs) and specific environmental exposures, controlling for overall genetic relatedness using a genomic relatedness matrix restricted maximum-likelihood model. In a UK-representative sample (n = 6,710), we find widespread covariation between offspring trait-associated polygenic variation and parental behavior and characteristics relevant to children's developmental outcomes-independently of population stratification. For instance, offspring genetic risk for schizophrenia was associated with paternal age (R² = 0.002; P = 1e-04), and offspring education-associated variation was associated with variance in breastfeeding (R² = 0.021; P = 7e-30), maternal smoking during pregnancy (R² = 0.008; P = 5e-13), parental smacking (R² = 0.01; P = 4e-15), household income (R² = 0.032; P = 1e-22), watching television (R² = 0.034; P = 5e-47), and maternal education (R² = 0.065; P = 3e-96). Education-associated polygenic variation also captured covariation between environmental exposures and children's inattention/hyperactivity, conduct problems, and educational achievement. The finding that genetic variation identified by trait GWASs partially captures environmental risk factors or protective factors has direct implications for risk prediction models and the interpretation of GWAS findings.

A hierarchical causal taxonomy of psychopathology across the life span

We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a hierarchy of increasingly specific etiologic influences. Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the heterogeneity of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the 3 levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology. (PsycINFO Database Record

Neuropsychological and neuroimaging evidence for the involvement of the frontal lobes in depression: 20 years on

In 1997, neuropsychological and neuroimaging evidence supported the involvement of the frontal lobes and indeed the brain in depression. This was a challenge to conventional phenomenology and linked with the imperative to use neuroscience to understand major mental illness. Since that time, we are seeing ever more convincing evidence for the genetic basis of mental illness (including depression), relevant abnormality in grey and white matter and neuropsychological analysis of brain function. It has proved more difficult to pin down structural abnormality in major depression at the cellular level, but a focus on glial cells is increasingly justified by the evidence. Neuroscience continues to be a buttress against anti-scientific impulses in psychiatry and can help attract young people to enter it as a profession.

Financial difficulties but not other types of recent negative life events show strong interactions with 5-HTTLPR genotype in the development of depressive symptoms

Several studies indicate that 5-HTTLPR mediates the effect of childhood adversity in the development of depression, while results are contradictory for recent negative life events. For childhood adversity the interaction with genotype is strongest for sexual abuse, but not for other types of childhood maltreatment; however, possible interactions with specific recent life events have not been investigated separately. The aim of our study was to investigate the effect of four distinct types of recent life events in the development of depressive symptoms in a large community sample. Interaction between different types of recent life events measured by the List of Threatening Experiences and the 5-HTTLPR genotype on current depression measured by the depression subscale and additional items of the Brief Symptom Inventory was investigated in 2588 subjects in Manchester and Budapest. Only a nominal interaction was found between life events overall and 5-HTTLPR on depression, which failed to survive correction for multiple testing. However, subcategorising life events into four categories showed a robust interaction between financial difficulties and the 5-HTTLPR genotype, and a weaker interaction in the case of illness/injury. No interaction effect for the other two life event categories was present. We investigated a general non-representative sample in a cross-sectional approach. Depressive symptoms and life event evaluations were self-reported. The 5-HTTLPR polymorphism showed a differential interaction pattern with different types of recent life events, with the strongest interaction effects of financial difficulties on depressive symptoms. This specificity of interaction with only particular types of life events may help to explain previous contradictory findings.

GENOME-WIDE ASSOCIATION STUDY (GWAS) AND GENOME-WIDE BY ENVIRONMENT INTERACTION STUDY (GWEIS) OF DEPRESSIVE SYMPTOMS IN AFRICAN AMERICAN AND HISPANIC/LATINA WOMEN

BACKGROUND

Genome-wide association studies (GWAS) have made little progress in identifying variants linked to depression. We hypothesized that examining depressive symptoms and considering gene-environment interaction (GxE) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome-wide by environment interaction study (GWEIS) of depressive symptoms.

METHODS

Using data from the SHARe cohort of the Women's Health Initiative, comprising African Americans (n = 7,179) and Hispanics/Latinas (n = 3,138), we examined genetic main effects and GxE with stressful life events and social support. We also conducted a heritability analysis using genome-wide complex trait analysis (GCTA). Replication was attempted in four independent cohorts.

RESULTS

No SNPs achieved genome-wide significance for main effects in either discovery sample. The top signals in African Americans were rs73531535 (located 20 kb from GPR139, P = 5.75 × 10(-8) ) and rs75407252 (intronic to CACNA2D3, P = 6.99 × 10(-7) ). In Hispanics/Latinas, the top signals were rs2532087 (located 27 kb from CD38, P = 2.44 × 10(-7) ) and rs4542757 (intronic to DCC, P = 7.31 × 10(-7) ). In the GEWIS with stressful life events, one interaction signal was genome-wide significant in African Americans (rs4652467; P = 4.10 × 10(-10) ; located 14 kb from CEP350). This interaction was not observed in a smaller replication cohort. Although heritability estimates for depressive symptoms and stressful life events were each less than 10%, they were strongly genetically correlated (rG = 0.95), suggesting that common variation underlying self-reported depressive symptoms and stressful life event exposure, though modest on their own, were highly overlapping in this sample.

CONCLUSIONS

Our results underscore the need for larger samples, more GEWIS, and greater investigation into genetic and environmental determinants of depressive symptoms in minorities.

Polygenic interactions with environmental adversity in the aetiology of major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene-environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD.

METHOD

The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them.

RESULTS

PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10(-6)). SLEs and CT were also associated with MDD status (p = 2.19 × 10(-4) and p = 5.12 × 10(-20), respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples.

CONCLUSIONS

CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene-environment interactions in complex traits.

Genome-Wide Estimates of Heritability for Social Demographic Outcomes

An increasing number of studies that are widely used in the demographic research community have collected genome-wide data from their respondents. It is therefore important that demographers have a proper understanding of some of the methodological tools needed to analyze such data. This article details the underlying methodology behind one of the most common techniques for analyzing genome-wide data, genome-wide complex trait analysis (GCTA). GCTA models provide heritability estimates for health, health behaviors, or indicators of attainment using data from unrelated persons. Our goal was to describe this model, highlight the utility of the model for biodemographic research, and demonstrate the performance of this approach under modifications to the underlying assumptions. The first set of modifications involved changing the nature of the genetic data used to compute genetic similarities between individuals (the genetic relationship matrix). We then explored the sensitivity of the model to heteroscedastic errors. In general, GCTA estimates are found to be robust to the modifications proposed here, but we also highlight potential limitations of GCTA estimates.

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

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

Top 10 Replicated Findings From Behavioral Genetics

In the context of current concerns about replication in psychological science, we describe 10 findings from behavioral genetic research that have replicated robustly. These are "big" findings, both in terms of effect size and potential impact on psychological science, such as linearly increasing heritability of intelligence from infancy (20%) through adulthood (60%). Four of our top 10 findings involve the environment, discoveries that could have been found only with genetically sensitive research designs. We also consider reasons specific to behavioral genetics that might explain why these findings replicate.

Familiality and SNP heritability of age at onset and episodicity in major depressive disorder

BACKGROUND

Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability).

METHOD

For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software.

RESULTS

Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity.

CONCLUSIONS

AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

A Behavior Genetic Analysis of Pleasant Events, Depressive Symptoms, and Their Covariation

Although pleasant events figure prominently in behavioral models of depression, little is known regarding characteristics that may predispose people to engage in pleasant events and derive pleasure from these events. The present study was conducted to evaluate genetic and environmental influences on the experience of pleasant events, depressive symptoms, and their covariation in a sample of 148 twin pairs. A multivariate twin modeling approach was used to examine the genetic and environmental covariance of pleasant events and depressive symptoms. Results indicated that the experience of pleasant events was moderately heritable and that the same genetic factors influence both the experience of pleasant events and depressive symptoms. These findings suggest that genetic factors may give rise to dispositional tendencies to experience both pleasant events and depression.

Genetic predisposition to schizophrenia associated with increased use of cannabis

Cannabis is the most commonly used illicit drug worldwide. With debate surrounding the legalization and control of use, investigating its health risks has become a pressing area of research. One established association is that between cannabis use and schizophrenia, a debilitating psychiatric disorder affecting ~1% of the population over their lifetime. Although considerable evidence implicates cannabis use as a component cause of schizophrenia, it remains unclear whether this is entirely due to cannabis directly raising risk of psychosis, or whether the same genes that increases psychosis risk may also increase risk of cannabis use. In a sample of 2082 healthy individuals, we show an association between an individual's burden of schizophrenia risk alleles and use of cannabis. This was significant both for comparing those who have ever versus never used cannabis (P=2.6 × 10(-4)), and for quantity of use within users (P=3.0 × 10(-3)). Although directly predicting only a small amount of the variance in cannabis use, these findings suggest that part of the association between schizophrenia and cannabis is due to a shared genetic aetiology. This form of gene-environment correlation is an important consideration when calculating the impact of environmental risk factors, including cannabis use.

Genotype-environment correlation in the era of DNA

One of John Loehlin’s many contributions to the field of behavioral genetics involves gene-environment (GE) correlation. The empirical base for GE correlation was research showing that environmental measures are nearly as heritable as behavioral measures and that genetic factors mediate correlations between environment and behavior. Attempts to identify genes responsible for these phenomena will come up against the ‘missing heritability’ problem that plagues DNA research on complex traits throughout the life sciences. However, DNA can also be used for quantitative genetic analyses of unrelated individuals (Genome-wide Complex Trait Analysis, GCTA) to investigate genetic influence on environmental measures and their behavioral correlates. A novel feature of GCTA is that it enables genetic analysis of family-level environments (e.g., parental socioeconomic status) and school-level environments (e.g., teaching quality) that cannot be investigated using within-family designs such as the twin method. An important implication of GE correlation is its shift from a passive model of the environment imposed on individuals to an active model in which individuals actively create their own experiences in part on the basis of their genetic propensities.

Word reading fluency: role of genome-wide single-nucleotide polymorphisms in developmental stability and correlations with print exposure

The genetic effects on individual differences in reading development were examined using genome-wide complex trait analysis (GCTA) in a twin sample. In unrelated individuals (one twin per pair, n = 2,942), the GCTA-based heritability of reading fluency was ~20%-29% at ages 7 and 12. GCTA bivariate results showed that the phenotypic stability of reading fluency from 7 to 12 years (r = 0.69) is largely driven by genetic stability (genetic r = 0.69). Genetic effects on print exposure at age 12 were moderate (~26%) and correlated with those influencing reading fluency at 12 (genetic r = 0.89), indicative of a gene-environment correlation. These findings were largely consistent with quantitative genetic twin analyses that used both twins in each pair (n = 1,066-1,409).

Timing of Stressful Life Events Affects Stability and Change of Neuroticism

Neuroticism is a predictor of many health problems. To study the determinants of within–subject change in neuroticism, three hypotheses were tested: (i) subjects who experienced stressful life events (SLEs) show an increase in neuroticism; (ii) high baseline neuroticism moderated this effect; and (iii) recent SLEs had a greater impact on neuroticism than distant SLEs. Data came from the Finnish Twin Cohort. Neuroticism data were collected in 1975 and 1981 and SLEs data in 1981 (n = 21 085). By entering baseline neuroticism as a predictor for neuroticism at follow–up, the outcome measure was change in neuroticism. Changes in neuroticism were predicted from SLE indices or their interaction with baseline neuroticism. Timing of SLEs was taken into account by distinguishing recent from distant SLEs. To control for confounding by shared genes and environments, both within–twin pair and between–twin pair effects were tested for monozygotic and dizygotic twin pairs separately. Neuroticism's six–year stability was high (r = .58, p < .001). Exposure to SLEs modestly increased neuroticism (βs > .55, ps < .001), unconfounded by shared genes. This effect was not moderated by high baseline neuroticism. Recent SLEs (.09 < βs < .15) had more impact than distant SLEs (.03 < βs < .11; ps < .01). In conclusion, the findings strongly supported a model of environmentally driven SLEs causing dynamic fluctuations around a person's set point of neuroticism. Copyright © 2013 John Wiley & Sons, Ltd.

Genetic influence on family socioeconomic status and children's intelligence

Environmental measures used widely in the behavioral sciences show nearly as much genetic influence as behavioral measures, a critical finding for interpreting associations between environmental factors and children's development. This research depends on the twin method that compares monozygotic and dizygotic twins, but key aspects of children's environment such as socioeconomic status (SES) cannot be investigated in twin studies because they are the same for children growing up together in a family. Here, using a new technique applied to DNA from 3000 unrelated children, we show significant genetic influence on family SES, and on its association with children's IQ at ages 7 and 12. In addition to demonstrating the ability to investigate genetic influence on between-family environmental measures, our results emphasize the need to consider genetics in research and policy on family SES and its association with children's IQ.

Does stress elicit depression? Evidence from clinical and preclinical studies

Exposure to stressful situations may induce or deteriorate an already existing depression. Stress-related depression can be elicited at an adolescent/adult age but evidence also shows that early adverse experiences even at the fetal stage may predispose the offspring for later development of depression. The hypothalamus-pituitary-adrenal axis (HPA-axis) plays a key role in regulating the stress response and dysregulation in the system has been linked to depression both in humans and in animal models. This chapter critically reviews clinical and preclinical findings that may explain how stress can cause depression, including HPA-axis changes and alterations beyond the HPA-axis. As stress does not elicit depression in the majority of the population, this motivated research to focus on understanding the biology underlying resilient versus sensitive subjects. Animal models of depression have contributed to a deeper understanding of these mechanisms. Findings from these models will be presented.

Genomics and the classification of mental illness: focus on broader categories

Coinciding with the release of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders, two recently published molecular genetics analyses suggest large overlaps in genetic liability to schizophrenia, bipolar disorder and major depressive disorder. This indicates that a broader category of severe mental illness may be an important target for future large-scale etiological and therapeutic investigations. Studies of patient groups not restricted to current diagnostic categories may lead to a genetically informed nosology.