Uncovering the genetic architecture of broad antisocial behavior through a genome-wide association study meta-analysis.

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, p = 6.32 × 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). Polygenic risk score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg = 0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg = 0.54), cognitive ability (intelligence rg = -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg = -0.58, father's age at death rg = -0.54). Our findings provide a starting point toward identifying critical biosocial risk mechanisms for the development of ASB.

Phenotypic and genetic factors associated with donation of DNA and consent to record linkage for prescription history in the Australian Genetics of Depression Study.

Samples can be prone to ascertainment and attrition biases. The Australian Genetics of Depression Study is a large publicly recruited cohort (n = 20,689) established to increase the understanding of depression and antidepressant treatment response. This study investigates differences between participants who donated a saliva sample or agreed to linkage of their records compared to those who did not. We observed that older, male participants with higher education were more likely to donate a saliva sample. Self-reported bipolar disorder, ADHD, panic disorder, PTSD, substance use disorder, and social anxiety disorder were associated with lower odds of donating a saliva sample, whereas anorexia was associated with higher odds of donation. Male and younger participants showed higher odds of agreeing to record linkage. Participants with higher neuroticism scores and those with a history of bipolar disorder were also more likely to agree to record linkage whereas participants with a diagnosis of anorexia were less likely to agree. Increased likelihood of consent was associated with increased genetic susceptibility to anorexia and reduced genetic risk for depression, and schizophrenia. Overall, our results show moderate differences among these subsamples. Most current epidemiological studies do not search for attrition biases at the genetic level. The possibility to do so is a strength of samples such as the AGDS. Our results suggest that analyses can be made more robust by identifying attrition biases both on the phenotypic and genetic level, and either contextualising them as a potential limitation or performing sensitivity analyses adjusting for them.

"Echoes of a dark past" is a history of maternal childhood maltreatment a perinatal risk factor for pregnancy and postpartum trauma experiences? A longitudinal study.

BACKGROUND: Although associations between maternal exposure to adverse childhood experiences (ACEs) and perinatal anxiety and depression are established, there is a paucity of information about the associations between ACEs and perinatal trauma and perinatal post-traumatic stress outcomes. For the purposes of this article, perinatal trauma is defined as a very frightening or distressing event that may result in psychological harm. The event must have been related to conception, pregnancy, birth, and up to 12 months postpartum. METHODS: Women recruited at an antenatal appointment (n = 262) were invited to complete online surveys at two-time points; mid-pregnancy and eight weeks after the estimated date of delivery. The ACE Q 10-item self-reporting tool and a perinatal trauma screen related to the current and/or a previous perinatal period were completed. If the perinatal trauma screen was positive at either time point in the study, women were invited to complete a questionnaire examining symptoms of perinatal post-traumatic stress disorder and, if consenting, a clinical interview where the Post-traumatic Symptoms Scale was administered. RESULTS: Sixty women (22.9%) reported four or more ACEs. These women were almost four times more likely to endorse perinatal trauma, when compared with those who either did not report ACEs (OR = 3.6, CI 95% 1.74 - 7.36, p < 0.001) or had less than four ACEs (OR = 3.9, CI 95% 2.037.55, p < 0.001). A 6-sevenfold increase in perinatal trauma was seen amongst women who reported having at least one ACE related to abuse (OR = 6.23, CI 95% 3.32-11.63, p < 0.001) or neglect (OR = 6.94, CI 95% 2.95-16.33, p < 0.001). The severity of perinatal-PTSD symptoms for those with perinatal trauma in pregnancy was significantly higher in those women exposed to at least one ACE related to abuse. CONCLUSIONS: Awareness of maternal exposure to childhood adversity/maltreatment is critical to providing trauma-informed approaches in the perinatal setting. Our study suggests that routine screening for ACEs in pregnancy adds clinical value. This adds to previous research confirming the relationship between ACEs and mental health complexities and suggests that ACEs influence perinatal mental health outcomes.

Preliminary results from the Australian Genetics of Bipolar Disorder Study: A nation-wide cohort.

OBJECTIVE: The Australian Genetics of Bipolar Disorder Study is a nation-wide cohort of adults living with bipolar disorder. The study aims to detect the relationships between genetic risk, symptom severity, and the lifetime prevalence of bipolar disorder, treatment response and medication side effects, and patterns and costs of health care usage. METHODS: A total of 6682 participants (68.3% female; aged 44.8 ± 13.6 years [range = 18-90]) were recruited in three waves: a nation-wide media campaign, a mail-out based on prescriptions for lithium carbonate and through the Australian Genetics of Depression Study. Participants completed a self-report questionnaire. A total of 4706 (70%) participants provided a saliva sample and were genotyped and 5506 (82%) consented to record linkage of their Pharmaceutical and Medicare Benefits Schedule data. RESULTS: Most participants were living with bipolar I disorder (n = 4068) while 1622 participants were living with bipolar II disorder and 992 with sub-threshold bipolar disorder. The mean age of bipolar disorder diagnosis was 32.7 ± 11.6 years but was younger in bipolar I (p = 2.0E-26) and females (p = 5.7E-23). Excluding depression with onset prior to bipolar disorder diagnosis, 64.5% of participants reported one or more co-occurring psychiatric disorders: most commonly generalised anxiety disorder (43.5%) and posttraumatic stress disorder (20.7%). Adverse drug reactions were common and resulted in discontinuation rates ranging from 33.4% for lithium to 63.0% for carbamazepine. CONCLUSION: Our findings highlight the high rate of comorbidities and adverse drug reactions among adults living with bipolar disorder in the general Australian population. Future genomic analyses focus on identifying genetic variants influencing pharmacotherapy treatment response and side effects.

Ten years of enhancing neuro-imaging genetics through meta-analysis: An overview from the ENIGMA Genetics Working Group.

Here we review the motivation for creating the enhancing neuroimaging genetics through meta-analysis (ENIGMA) Consortium and the genetic analyses undertaken by the consortium so far. We discuss the methodological challenges, findings, and future directions of the genetics working group. A major goal of the working group is tackling the reproducibility crisis affecting "candidate gene" and genome-wide association analyses in neuroimaging. To address this, we developed harmonized analytic methods, and support their use in coordinated analyses across sites worldwide, which also makes it possible to understand heterogeneity in results across sites. These efforts have resulted in the identification of hundreds of common genomic loci robustly associated with brain structure. We have found both pleiotropic and specific genetic effects associated with brain structures, as well as genetic correlations with psychiatric and neurological diseases.

Perinatal depression is associated with a higher polygenic risk for major depressive disorder than non-perinatal depression.

BACKGROUND: Distinctions between major depressive disorder (MDD) and perinatal depression (PND) reflect varying views of PND, from a unique etiological subtype of MDD to an MDD episode that happens to coincide with childbirth. This case-control study investigated genetic differences between PND and MDD outside the perinatal period (non-perinatal depression or NPD). METHODS: We conducted a genome-wide association study using PND cases (Edinburgh Postnatal Depression Scale score ≥ 13) from the Australian Genetics of Depression Study 2018 data (n = 3804) and screened controls (n = 6134). Results of gene-set enrichment analysis were compared with those of women with non-PND. For six psychiatric disorders/traits, genetic correlations with PND were evaluated, and logistic regression analysis reported polygenic score (PGS) association with both PND and NPD. RESULTS: Genes differentially expressed in ovarian tissue were significantly enriched (stdBeta = 0.07, p = 3.3e-04), but were not found to be associated with NPD. The genetic correlation between PND and MDD was 0.93 (SE = 0.07; p = 3.5e-38). Compared with controls, PGS for MDD are higher for PND cases (odds ratio [OR] = 1.8, confidence interval [CI] = [1.7-1.8], p = 9.5e-140) than for NPD cases (OR = 1.6, CI = [1.5-1.7], p = 1.2e-49). Highest risk is for those reporting both antenatal and postnatal depression, irrespective of prior MDD history. CONCLUSIONS: PND has a high genetic overlap with MDD, but points of distinction focus on differential expression in ovarian tissue and higher MDD PGS, particularly for women experiencing both antenatal and postpartum PND.

The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area.

Structural brain changes along the lineage leading to modern Homo sapiens contributed to our distinctive cognitive and social abilities. However, the evolutionarily relevant molecular variants impacting key aspects of neuroanatomy are largely unknown. Here, we integrate evolutionary annotations of the genome at diverse timescales with common variant associations from large-scale neuroimaging genetic screens. We find that alleles with evidence of recent positive polygenic selection over the past 2000-3000 years are associated with increased surface area (SA) of the entire cortex, as well as specific regions, including those involved in spoken language and visual processing. Therefore, polygenic selective pressures impact the structure of specific cortical areas even over relatively recent timescales. Moreover, common sequence variation within human gained enhancers active in the prenatal cortex is associated with postnatal global SA. We show that such variation modulates the function of a regulatory element of the developmentally relevant transcription factor HEY2 in human neural progenitor cells and is associated with structural changes in the inferior frontal cortex. These results indicate that non-coding genomic regions active during prenatal cortical development are involved in the evolution of human brain structure and identify novel regulatory elements and genes impacting modern human brain structure.

Co-Inheritance of Variation in All-Cause Mortality and Biochemical Risk Factors.

Biomarkers may be useful endophenotypes for genetic studies if they share genetic sources of variation with the outcome, for example, with all-cause mortality. Australian adult study participants who had reported their parental survival information were included in the study: 14,169 participants had polygenic risk scores (PRS) from genotyping and up to 13,365 had biomarker results. We assessed associations between participants' biomarker results and parental survival, and between biomarker results and eight parental survival PRS at varying p-value cut-offs. Survival in parents was associated with participants' serum bilirubin, C-reactive protein, HDL cholesterol, triglycerides and uric acid, and with LDL cholesterol for participants' fathers but not for their mothers. PRS for all-cause mortality were associated with liver function tests (alkaline phosphatase, butyrylcholinesterase, gamma-glutamyl transferase), metabolic tests (LDL and HDL cholesterol, triglycerides, uric acid), and acute-phase reactants (C-reactive protein, globulins). Association between offspring biomarker results and parental survival demonstrates the existence of familial effects common to both, while associations between biomarker results and PRS for mortality favor at least a partial genetic cause of this covariation. Identification of genetic loci affecting mortality-associated biomarkers offers a route to the identification of additional loci affecting mortality.

Educational Attainment Polygenic Scores: Examining Evidence for Gene-Environment Interplay with Adolescent Alcohol, Tobacco and Cannabis Use.

Genes associated with educational attainment may be related to or interact with adolescent alcohol, tobacco and cannabis use. Potential gene-environment interplay between educational attainment polygenic scores (EA-PGS) and adolescent alcohol, tobacco, and cannabis use was evaluated with a series of regression models fitted to data from a sample of 1871 adult Australian twins. All models controlled for age, age2, cohort, sex and genetic ancestry as fixed effects, and a genetic relatedness matrix was included as a random effect. Although there was no evidence that adolescent alcohol, tobacco or cannabis use interacted with EA-PGS to influence educational attainment, there was a significant, positive gene-environment correlation with adolescent alcohol use at all PGS thresholds (ps <.02). Higher EA-PGS were associated with an increased likelihood of using alcohol as an adolescent (ΔR2 ranged from 0.5% to 1.1%). The positive gene-environment correlation suggests a complex relationship between educational attainment and alcohol use that is due to common genetic factors.

Two genetic analyses to elucidate causality between body mass index and personality.

BACKGROUND/OBJECTIVES: Many personality traits correlate with BMI, but the existence and direction of causal links between them are unclear. If personality influences BMI, knowing this causal direction could inform weight management strategies. Knowing that BMI instead influences personality would contribute to a better understanding of the mechanisms of personality development and the possible psychological effects of weight change. We tested the existence and direction of causal links between BMI and personality. SUBJECTS/METHODS: We employed two genetically informed methods. In Mendelian randomization, allele scores were calculated to summarize genetic propensity for the personality traits neuroticism, worry, and depressive affect and used to predict BMI in an independent sample (N = 3 541). Similarly, an allele score for BMI was used to predict eating-specific and domain-general phenotypic personality scores (PPSs; aggregate scores of personality traits weighted by BMI). In a direction of causation (DoC) analysis, twin data from five countries (N = 5424) were used to assess the fit of four alternative models: PPSs influencing BMI, BMI influencing PPSs, reciprocal causation, and no causation. RESULTS: In Mendelian randomization, the allele score for BMI predicted domain-general (ß = 0.05; 95% CI: 0.02, 0.08; P = 0.003) and eating-specific PPS (ß = 0.06; 95% CI: 0.03, 0.09; P < 0.001). The allele score for worry also predicted BMI (ß = -0.05; 95% CI: -0.08, -0.02; P < 0.001), while those for neuroticism and depressive affect did not (P ≥ 0.459). In DoC, BMI similarly predicted domain-general (ß = 0.21; 95% CI:, 0.18, 0.24; P < 0.001) and eating-specific personality traits (ß = 0.19; 95% CI:, 0.16, 0.22; P < 0.001), suggesting causality from BMI to personality traits. In exploratory analyses, links between BMI and domain-general personality traits appeared reciprocal for higher-weight individuals (BMI > ~25). CONCLUSIONS: Although both genetic analyses suggested an influence of BMI on personality traits, it is not yet known if weight management interventions could influence personality. Personality traits may influence BMI in turn, but effects in this direction appeared weaker.

Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being.

The distinction between genetic influences on the covariance (or bivariate heritability) and genetic correlations in bivariate twin models is often not well-understood or only one is reported while the results show distinctive information about the relation between traits. We applied bivariate twin models in a large sample of adolescent twins, to disentangle the association between well-being (WB) and four complex traits (optimism, anxious-depressed symptoms (AD), aggressive behaviour (AGG), and educational achievement (EA)). Optimism and AD showed respectively a strong positive and negative phenotypic correlation with WB, the negative correlation of WB and AGG is lower and the correlation with EA is nearly zero. All four traits showed a large genetic contribution to the covariance with well-being. The genetic correlations of well-being with optimism and AD are strong and smaller for AGG and EA. We used the results of the models to explain what information is retrieved based on the bivariate heritability versus the genetic correlations and the (clinical) implications.

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

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

Educational attainment of same-sex and opposite-sex dizygotic twins: An individual-level pooled study of 19 twin cohorts.

Comparing twins from same- and opposite-sex pairs can provide information on potential sex differences in a variety of outcomes, including socioeconomic-related outcomes such as educational attainment. It has been suggested that this design can be applied to examine the putative role of intrauterine exposure to testosterone for educational attainment, but the evidence is still disputed. Thus, we established an international database of twin data from 11 countries with 88,290 individual dizygotic twins born over 100 years and tested for differences between twins from same- and opposite-sex dizygotic pairs in educational attainment. Effect sizes with 95% confidence intervals (CI) were estimated by linear regression models after adjusting for birth year and twin study cohort. In contrast to the hypothesis, no difference was found in women (ß = -0.05 educational years, 95% CI -0.11, 0.02). However, men with a same-sex co-twin were slightly more educated than men having an opposite-sex co-twin (ß = 0.14 educational years, 95% CI 0.07, 0.21). No consistent differences in effect sizes were found between individual twin study cohorts representing Europe, the USA, and Australia or over the cohorts born during the 20th century, during which period the sex differences in education reversed favoring women in the latest birth cohorts. Further, no interaction was found with maternal or paternal education. Our results contradict the hypothesis that there would be differences in the intrauterine testosterone levels between same-sex and opposite-sex female twins affecting education. Our findings in men may point to social dynamics within same-sex twin pairs that may benefit men in their educational careers.

Investigating perceived heritability of mental health disorders and attitudes toward genetic testing in the United States, United Kingdom, and Australia.

Our beliefs about the heritability of psychiatric traits may influence how we respond to the use of genetic information in this area. In the present study, we aim to inform future education campaigns as well as genetic counseling interventions by exploring common fears and misunderstandings associated with learning about genetic predispositions for mental health disorders. We surveyed 3,646 genetic research participants from Australia, and 960 members of the public from the United Kingdom, and the United States, and evaluated attitudes toward psychiatric genetic testing. Participants were asked hypothetical questions about their interest in psychiatric genetic testing, perceived usefulness of psychiatric genetic testing, and beliefs about malleability of behavior, among others. We also asked them to estimate the heritability of alcohol dependence, schizophrenia, and major depression. We found a high interest in psychiatric genetic testing. In most cases, more than a third of the participants showed serious concerns related to learning about personal genetic predisposition, such as not wanting to have children if they knew they had a high genetic predisposition, or not wanting to choose a partner with a high genetic predisposition for a mental health problem. Finally, we found a significant association between most participants' attitudes and their lay estimates of heritability, which highlights the complexity of educating the public about genetics.

Nick Martin's Contribution to GxE Research.

The study and identification of genotype-environment interactions (GxE) has been a hot topic in the field of human genetics for several decades. Yet the extent to which GxE contributes to human behavior variability, and its mechanisms, remains largely unknown. Nick Martin has contributed important advances to the field of GxE for human behavior, which include methodological developments, novel analyses and reviews. Here, we will first review Nick's contributions to the GxE research, which started during his PhD and consistently appears in many of his over 1000 publications. Then, we recount a project that led to an article testing the diathesis-stress model for the origins of depression. In this publication, we observed the presence of an interaction between polygenic risk scores for depression (the risk in our 'genotype') and stressful life events (the experiences from our 'environment'), which provided the first empirical support of this model.

The Role of the Environment in Overweight and Eating Behavior Variability: Insights from a Multivariate Twin Study.

Research has emphasized the genetic basis of individual differences in body mass index (BMI); however, genetic factors cannot explain the rapid rise of obesity. Eating behaviors have been stipulated to be the behavioral expression of genetic risk in an obesogenic environment. In this study, we decompose variation and covariation between three key eating behaviors and BMI in a sample of 698 participants, consisting of 167 monozygotic, 150 dizygotic complete same-sex female twins and 64 incomplete pairs from a population-based twin registry in the southeast of Spain, The Murcia Twin Registry. Phenotypes were emotional eating, uncontrolled eating and cognitive restraint, measured by the Three Factor Eating Questionnaire and objectively measured BMI. Variation in eating behaviors was driven by nonshared environmental factors (range: 56%-65%), whereas shared environmental and genetic factors were secondary. All three eating behaviors were correlated with BMI (r = .19-.25). Nonshared environmental factors explained the covariations (Emotional eating-Uncontrolled eating: rE = .54, 95% CI [.43, .64]; BMI-Cognitive restraint: rE = .15, 95% CI [.01, .28]). In contrast to BMI, individual differences in eating behaviors are mostly explained by nonshared environmental factors, which also accounted for the phenotypic correlation between eating behaviors and BMI. Due to the sample size, analyses were underpowered to detect contributions of additive genetic or shared environmental factors to variation and covariation of the phenotypes. Although more research is granted, these results support that eating behaviors could be viable intervention targets to help individuals maintain a healthy weight.

Comparison of Familial, Polygenic and Biochemical Predictors of Mortality.

Mortality risk is known to be associated with many physiological or biochemical risk factors, and polygenic risk scores (PRSs) may offer an additional or alternative approach to risk stratification. We have compared the predictive value of common biochemical tests, PRSs and information on parental survival in a cohort of twins and their families. Common biochemical test results were available for up to 13,365 apparently healthy men and women, aged 17-93 years (mean 49.0, standard deviation [SD] 13.7) at blood collection. PRSs for longevity were available for 14,169 study participants and reported parental survival for 25,784 participants. A search for information on date and cause of death was conducted through the Australian National Death Index, with median follow-up of 11.3 years. Cox regression was used to evaluate associations with mortality from all causes, cancers, cardiovascular diseases and other causes. Linear relationships with all-cause mortality were strongest for C-reactive protein, gamma-glutamyl transferase, glucose and alkaline phosphatase, with hazard ratios (HRs) of 1.16 (95% CI [1.07, 1.24]), 1.15 (95% CI 1.04-1.21), 1.13 (95% CI [1.08, 1.19]) and 1.11 (95% CI [1.05, 1.88]) per SD difference, respectively. Significant nonlinear effects were found for urea, uric acid and butyrylcholinesterase. Lipid risk factors were not statistically significant for mortality in our cohort. Family history and PRS showed weaker but significant associations with survival, with HR in the range 1.05 to 1.09 per SD difference. In conclusion, biochemical tests currently predict long-term mortality more strongly than genetic scores based on genotyping or on reported parental survival.

Genetic and Environmental Causes of Individual Differences in Borderline Personality Disorder Features and Loneliness are Partially Shared.

Loneliness is related to mental and somatic health outcomes, including borderline personality disorder. Here, we analyze the sources of variation that are responsible for the relationship between borderline personality features (including four dimensions, affective instability, identity disturbance, negative relationships, self-harm and a total score) and loneliness. Using genetically informative data from two large nonclinical samples of adult twin pairs from Australia and the Netherlands (N = 11,329), we estimate the phenotypic, genetic and environmental correlations between self-reported borderline personality features and loneliness. Individual differences in borderline personality and loneliness were best explained by additive genetic factors with heritability estimates h2 = 41% for the borderline personality total score and h2 = 36% for loneliness, with the remaining variation explained by environmental influences that were not shared by twins from the same pair. Genetic and environmental factors influencing borderline personality (total score and four subscales separately) were also partial causes of loneliness. The correlation between loneliness and the borderline personality total score was rph = .51. The genetic correlation was estimated at rg = .64 and the environmental correlation at re = .40. Our study suggests common etiological factors in loneliness and borderline personality features.

Neuroticism as a Predictor of Frailty in Old Age: A Genetically Informative Approach.

OBJECTIVE: Neuroticism is associated with poor health outcomes, but its contribution to the accumulation of health deficits in old age, that is, the frailty index, is largely unknown. We aimed to explore associations between neuroticism and frailty cross-sectionally and longitudinally, and to investigate the contribution of shared genetic influences. METHODS: Data were derived from the UK Biobank (UKB; n = 274,951), the Australian Over 50's Study (AO50; n = 2849), and the Swedish Twin Registry (Screening Across the Lifespan of Twins Study [SALT], n = 18,960; The Swedish Adoption/Twin Study of Aging [SATSA], n = 1365). Associations between neuroticism and the frailty index were investigated using regression analysis cross-sectionally in UKB, AO50, and SATSA and longitudinally in SALT (25-29 years of follow-up) and SATSA (6 and 23 years of follow-up). The co-twin control method was applied to explore the contribution of underlying shared familial factors (SALT, SATSA, AO50). Genome-wide polygenic risk scores for neuroticism were used in all samples to further assess whether common genetic variants associated with neuroticism predict frailty. RESULTS: High neuroticism was consistently associated with greater frailty cross-sectionally (adjusted ß [95% confidence intervals] in UKB = 0.32 [0.32-0.33]; AO50 = 0.35 [0.31-0.39]; SATSA = 0.33 [0.27-0.39]) and longitudinally up to 29 years (SALT = 0.24 [0.22-0.25]; SATSA 6 years = 0.31 [0.24-0.38]; SATSA 23 years = 0.16 [0.07-0.25]). When adjusting for underlying shared genetic and environmental factors, the neuroticism-frailty association remained significant, although decreased. Polygenic risk scores for neuroticism significantly predicted frailty in the two larger samples (meta-analyzed total ß = 0.059 [0.055-0.062]). CONCLUSIONS: Neuroticism in midlife predicts frailty in late life. Neuroticism may have a causal influence on frailty, whereas both environmental and genetic influences, including neuroticism-associated common genetic variants, contribute to this relationship.

Shared and specific genetic risk factors for lifetime major depression, depressive symptoms and neuroticism in three population-based twin samples.

BACKGROUND: Vulnerability to depression can be measured in different ways. We here examine how genetic risk factors are inter-related for lifetime major depression (MD), self-report current depressive symptoms and the personality trait Neuroticism. METHOD: We obtained data from three population-based adult twin samples (Virginia n = 4672, Australia #1 n = 3598 and Australia #2 n = 1878) to which we fitted a common factor model where risk for 'broadly defined depression' was indexed by (i) lifetime MD assessed at personal interview, (ii) depressive symptoms, and (iii) neuroticism. We examined the proportion of genetic risk for MD deriving from the common factor v. specific to MD in each sample and then analyzed them jointly. Structural equation modeling was conducted in Mx. RESULTS: The best fit models in all samples included additive genetic and unique environmental effects. The proportion of genetic effects unique to lifetime MD and not shared with the broad depression common factor in the three samples were estimated as 77, 61, and 65%, respectively. A cross-sample mega-analysis model fit well and estimated that 65% of the genetic risk for MD was unique. CONCLUSION: A large proportion of genetic risk factors for lifetime MD was not, in the samples studied, captured by a common factor for broadly defined depression utilizing MD and self-report measures of current depressive symptoms and Neuroticism. The genetic substrate for MD may reflect neurobiological processes underlying the episodic nature of its cognitive, motor and neurovegetative manifestations, which are not well indexed by current depressive symptom and neuroticism.