Quantifying psychological resilience and elucidating its mechanisms using multivariate modelling

It is estimated that approximately 30% of individuals worldwide are affected by mental health problems during their lifetime. Currently, Major Depressive Disorder (MDD) is one of the most prevalent psychiatric disorders and a leading cause of non-lethal disability worldwide. However, despite exposure to known risk factors for MDD, human responses to it vary widely. Whilst some individuals develop MDD, others develop only mild and transient symptoms or no depressive symptomology at all. This ability to 'bounce back' from or 'escape‘ the development of psychiatric illness is referred to as psychological resilience (Chapter 1). Scientific and clinical interest in resilience has grown exponentially over recent decades, but wide discrepancies are still found in both its definition and measurement. As such, resilience is rarely measured directly, but inferred from the measurement of two specific points of convergence; adversity (its antecedents) and positive adaptation (its consequences). Whilst the study of adversity and positive adaptation has informed our knowledge of resilience it often fails to consider other putative risk factors for MDD (such as genetics), or potential protective factors that may foster resilience despite risk. More recently, examining protective factors have become a focus of research in relation to resilience. This research suggests that numerous protective factors coalesce to contribute to resilient outcomes which give rise to a dynamic resilience process that varies contextually and temporally. Although investigating resilience may be expected to reveal similar findings to studying MDD itself, it does represent a new facet to scientific and clinical research. Specifically, resilience focuses on intervention long before the development of MDD when effects on subsequent suffering may be ameliorated. For this reason, it is imperative to address the concept of resilience, concentrating on the core components of adversity, positive adaptation and protective factors, to move beyond description towards an understanding of individual differences in resilience (Chapter 2). In this thesis, three studies will be presented which aim to examine psychological resilience from multiple perspectives to further delineate the concept. In Chapter 3, the associations and interactions between neuroticism and general intelligence (g) on MDD, and psychological distress were examined in GS:SFHS (Generation Scotland: Scottish Family Health Study) to investigate whether g mitigates the detrimental effects of neuroticism on mental health, as such an association has previously been identified for physical health and mortality. A larger replication was also performed in UK Biobank using a self-reported measure of depression. Across two large samples it was found that intelligence provides protection against psychological distress and self-reported depression in individuals high in neuroticism, but intelligence confers no such protection against clinical MDD in those high in neuroticism. In Chapter 4, a new dataset is presented which was designed to investigate psychological resilience and mental health. Specifically, the STRADL (Stratifying Resilience and Depression Longitudinally) dataset aimed to re-contact existing GS:SFHS participants to obtain repeat measures of MDD and psychological distress in addition to obtaining data on resilience, coping style and adverse life experiences. This dataset has the potential to identify mechanisms and pathways to resilience but also elucidate causal mechanisms and pathways of depression sub-types. Chapter 5 investigated whether neuroticism and resilience are downstream mediators of genetic risk for depression, and whether they contribute independently to such risk. Specifically, the moderating and mediating relationships between polygenic risk scores (PRS) for depression, neuroticism, resilience, and both clinical and self-reported MDD were examined in STRADL. Regression analyses indicated that neuroticism and PRS for depression independently associated with increased risk for both clinical and self-reported MDD, whereas resilience associated with reduced risk. Structural equation modelling suggested that polygenic risk for depression associates with vulnerability for both clinical and self-reported MDD through two partially independent mediating mechanisms in which neuroticism increases vulnerability and resilience reduces it. In Chapter 6, the proportion of phenotypic variance that is attributable to genetic and shared-familial environment was estimated for resilience and three main coping styles; task-, emotion-, and avoidance-oriented coping. Bivariate analyses were conducted to estimate the genetic correlations between these traits and neuroticism. Our results indicate that common genetics affect both resilience and coping style. However, in addition, early shared-environmental effects from the nuclear family influence resilience whereas recent shared-environment effects from a spouse influence coping style. Furthermore, strong genetic overlap between resilience, emotion-oriented coping, and neuroticism suggests a relationship whereby genetic factors that increase negative emotionality lead to decreased resilience. These studies highlight the necessity for complementary multivariate techniques in resilience research to elucidate tractable methodologies to potentially identify mechanisms and modifiable risk factors to protect against psychiatric illness (Chapter 7)

Moral Chivalry: Gender and Harm Sensitivity Predict Costly Altruism.

Moral perceptions of harm and fairness are instrumental in guiding how an individual navigates moral challenges. Classic research documents that the gender of a target can affect how people deploy these perceptions of harm and fairness. Across multiple studies, we explore the effect of an individual's moral orientations (their considerations of harm and justice) and a target's gender on altruistic behavior. Results reveal that a target's gender can bias one's readiness to engage in harmful actions and that a decider's considerations of harm-but not fairness concerns-modulate costly altruism. Together, these data illustrate that moral choices are conditional on the social nature of the moral dyad: Even under the same moral constraints, a target's gender and a decider's gender can shift an individual's choice to be more or less altruistic, suggesting that gender bias and harm considerations play a significant role in moral cognition

Moral Chivalry: Gender and Harm Sensitivity Predict Costly Altruism

Moral perceptions of harm and fairness are instrumental in guiding how an individual navigates moral challenges. Classic research documents that the gender of a target can affect how people deploy these perceptions of harm and fairness. Across multiple studies, we explore the effect of an individual’s moral orientations (their considerations of harm and justice) and a target’s gender on altruistic behavior. Results reveal that a target’s gender can bias one’s readiness to engage in harmful actions and that a decider’s considerations of harm—but not fairness concerns—modulate costly altruism. Together, these data illustrate that moral choices are conditional on the social nature of the moral dyad: Even under the same moral constraints, a target’s gender and a decider’s gender can shift an individual’s choice to be more or less altruistic, suggesting that gender bias and harm considerations play a significant role in moral cognition

A validation of the diathesis-stress model for depression in Generation Scotland

Abstract Depression has well-established influences from genetic and environmental risk factors. This has led to the diathesis-stress theory, which assumes a multiplicative gene-by-environment interaction (GxE) effect on risk. Recently, Colodro-Conde et al. empirically tested this theory, using the polygenic risk score for major depressive disorder (PRS, genes) and stressful life events (SLE, environment) effects on depressive symptoms, identifying significant GxE effects with an additive contribution to liability. We have tested the diathesis-stress theory on an independent sample of 4919 individuals. We identified nominally significant positive GxE effects in the full cohort (R 2 = 0.08%, p = 0.049) and in women (R 2 = 0.19%, p = 0.017), but not in men (R 2 = 0.15%, p = 0.07). GxE effects were nominally significant, but only in women, when SLE were split into those in which the respondent plays an active or passive role (R 2 = 0.15%, p = 0.038; R 2 = 0.16%, p = 0.033, respectively). High PRS increased the risk of depression in participants reporting high numbers of SLE (p = 2.86 × 10−4). However, in those participants who reported no recent SLE, a higher PRS appeared to increase the risk of depressive symptoms in men (β = 0.082, p = 0.016) but had a protective effect in women (β = −0.061, p = 0.037). This difference was nominally significant (p  = 0.017). Our study reinforces the evidence of additional risk in the aetiology of depression due to GxE effects. However, larger sample sizes are required to robustly validate these findings

Affective enhancement of working memory is maintained in depression.

We currently know little about how performance on assessments of working memory capacity (WMC) that are designed to mirror the concurrent task demands of daily life are impacted by the presence of affective information, nor how those effects may be modulated by depression-a syndrome where sufferers report global difficulties with executive processing. Across 3 experiments, we investigated WMC for sets of neutral words in the context of processing either neutral or affective (depressogenic) sentences, which had to be judged on semantic accuracy (Experiments 1 and 2) or self-reference (Experiment 3). Overall, WMC was significantly better in the context of depressogenic compared with neutral sentences. However, there was no support for this effect being modulated by symptoms of depression (Experiment 1) or the presence of recurrent major depressive disorder (MDD; Experiments 2 and 3). Implications of these findings for cognitive theories of the role of WM in depression are discussed in the context of a growing body of research showing no support for a differential impact of depressogenic compared with neutral information on WM accuracy. (PsycINFO Database Recor

Genome-wide association study of antidepressant treatment resistance in a population-based cohort using health service prescription data and meta-analysis with GENDEP

Antidepressants demonstrate modest response rates in the treatment of major depressive disorder (MDD). Despite previous genome-wide association studies (GWAS) of antidepressant treatment response, the underlying genetic factors are unknown. Using prescription data in a population and family-based cohort (Generation Scotland: Scottish Family Health Study; GS:SFHS), we sought to define a measure of (a) antidepressant treatment resistance and (b) stages of antidepressant resistance by inferring antidepressant switching as non-response to treatment. GWAS were conducted separately for antidepressant treatment resistance in GS:SFHS and the Genome-based Therapeutic Drugs for Depression (GENDEP) study and then meta-analysed (meta-analysis n = 4213, cases = 358). For stages of antidepressant resistance, a GWAS on GS:SFHS only was performed (n = 3452). Additionally, we conducted gene-set enrichment, polygenic risk scoring (PRS) and genetic correlation analysis. We did not identify any significant loci, genes or gene sets associated with antidepressant treatment resistance or stages of resistance. Significant positive genetic correlations of antidepressant treatment resistance and stages of resistance with neuroticism, psychological distress, schizotypy and mood disorder traits were identified. These findings suggest that larger sample sizes are needed to identify the genetic architecture of antidepressant treatment response, and that population-based observational studies may provide a tractable approach to achieving the necessary statistical power

Moral Chivalry

xiv,128 hlm

What we say and what we do: The relationship between real and hypothetical moral choices

► We show people are unable to appropriately judge outcomes of moral behaviour. ► Moral beliefs have weaker impact when there is a presence of significant self-gain. ► People make highly self-serving choices in real moral situations. ► Real moral choices contradict responses to simple hypothetical moral probes. ► Enhancing context can cause hypothetical decisions to mirror real moral decisions

Opas Sinulle joka autat, tuet, ohjaat, hoidat läheistäsi

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, r2=1.1%, p=2.5 x 10-25) and neuroticism (β =0.13, r2=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, r2=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 (rG=0.33, S.E.=0.08 ) and neuroticism (rG=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