Intriguing findings on genetic and environmental causation suggest a need to reframe the etiology of mental disorders. Molecular genetics shows that thousands of common and rare genetic variants ...contribute to mental illness. Epidemiological studies have identified dozens of environmental exposures that are associated with psychopathology. The effect of environment is likely conditional on genetic factors, resulting in gene‐environment interactions. The impact of environmental factors also depends on previous exposures, resulting in environment‐environment interactions. Most known genetic and environmental factors are shared across multiple mental disorders. Schizophrenia, bipolar disorder and major depressive disorder, in particular, are closely causally linked. Synthesis of findings from twin studies, molecular genetics and epidemiological research suggests that joint consideration of multiple genetic and environmental factors has much greater explanatory power than separate studies of genetic or environmental causation. Multi‐factorial gene‐environment interactions are likely to be a generic mechanism involved in the majority of cases of mental illness, which is only partially tapped by existing gene‐environment studies. Future research may cut across psychiatric disorders and address poly‐causation by considering multiple genetic and environmental measures across the life course with a specific focus on the first two decades of life. Integrative analyses of poly‐causation including gene‐environment and environment‐environment interactions can realize the potential for discovering causal types and mechanisms that are likely to generate new preventive and therapeutic tools.
Evidence suggests that childhood maltreatment may negatively affect not only the lifetime risk of depression but also clinically relevant measures of depression, such as course of illness and ...treatment outcome. The authors conducted the first meta-analysis to examine the relationship between childhood maltreatment and these clinically relevant measures of depression.
The authors conducted searches in MEDLINE, PsycINFO, and Embase for articles examining the association of childhood maltreatment with course of illness (i.e., recurrence or persistence) and with treatment outcome in depression that appeared in the literature before December 31, 2010. Recurrence was defined in terms of number of depressive episodes. Persistence was defined in terms of duration of current depressive episode. Treatment outcome was defined in terms of either a response (a 50% reduction in depression severity rating from baseline) or remission (a decrease in depression severity below a predefined clinical significance level).
A meta-analysis of 16 epidemiological studies (23,544 participants) suggested that childhood maltreatment was associated with an elevated risk of developing recurrent and persistent depressive episodes (odds ratio=2.27, 95% confidence interval CI=1.80–2.87). A meta-analysis of 10 clinical trials (3,098 participants) revealed that childhood maltreatment was associated with lack of response or remission during treatment for depression (odds ratio=1.43, 95% CI=1.11–1.83). Meta-regression analyses suggested that the results were not significantly affected by publication bias, choice of outcome measure, inclusion of prevalence or incidence samples, study quality, age of the sample, or lifetime prevalence of depression.
Childhood maltreatment predicts unfavorable course of illness and treatment outcome in depression.
Schizophrenia and other types of psychosis incur suffering, high health care costs and loss of human potential, due to the combination of early onset and poor response to treatment. Our ability to ...prevent or cure psychosis depends on knowledge of causal mechanisms. Molecular genetic studies show that thousands of common and rare variants contribute to the genetic risk for psychosis. Epidemiological studies have identified many environmental factors associated with increased risk of psychosis. However, no single genetic or environmental factor is sufficient to cause psychosis on its own. The risk of developing psychosis increases with the accumulation of many genetic risk variants and exposures to multiple adverse environmental factors. Additionally, the impact of environmental exposures likely depends on genetic factors, through gene-environment interactions. Only a few specific gene-environment combinations that lead to increased risk of psychosis have been identified to date. An example of replicable gene-environment interaction is a common polymorphism in the AKT1 gene that makes its carriers sensitive to developing psychosis with regular cannabis use. A synthesis of results from twin studies, molecular genetics, and epidemiological research outlines the many genetic and environmental factors contributing to psychosis. The interplay between these factors needs to be considered to draw a complete picture of etiology. To reach a more complete explanation of psychosis that can inform preventive strategies, future research should focus on longitudinal assessments of multiple environmental exposures within large, genotyped cohorts beginning early in life.
...depression is a heterogeneous entity experienced with various combinations of signs and symptoms, severity levels, and longitudinal trajectories. ...core features of the condition have been ...described over thousands of years, long before the advent of contemporary classifications, and in diverse communities and cultures. More efficient prevention of depression is likely to have powerful impacts on the Sustainable Development Goals for a country and the health of individuals and families. 5 The experiences of depression and recovery are unique for each individual Depression is the result of a set of factors, typically the interaction of proximal adversities with genetic, social, environmental, and developmental risk and resilience factors. Empowering individuals, families, and communities to work with professionals who can learn from their experiences and help demand the implementation of known preventive and therapeutic strategies and to hold health-care systems and decision makers accountable is vital. 7 A formulation is needed to personalise care Detection and diagnosis of depression on the basis of symptoms, function, and duration should be accompanied by a clinical review or formulation for each person, which takes into account individual values and preferences, life stories, and circumstances.
Evidence of marked variability in response among people exposed to the same environmental risk implies that individual differences in genetic susceptibility might be at work. The study of such ...Gene-by-Environment (GxE) interactions has gained momentum. In this article, the authors review research about one of the most extensive areas of inquiry: variation in the promoter region of the serotonin transporter gene (SLC6A4; also known as 5-HTT) and its contribution to stress sensitivity. Research in this area has both advanced basic science and generated broader lessons for studying complex diseases and traits. The authors evaluate four lines of evidence about the 5-HTT stress-sensitivity hypothesis: 1) observational studies about the serotonin transporter linked polymorphic region (5-HTTLPR), stress sensitivity, and depression in humans; 2) experimental neuroscience studies about the 5-HTTLPR and biological phenotypes relevant to the human stress response; 3) studies of 5-HTT variation and stress sensitivity in nonhuman primates; and 4) studies of stress sensitivity and genetically engineered 5-HTT mutations in rodents. The authors then dispel some misconceptions and offer recommendations for GxE research. The authors discuss how GxE interaction hypotheses can be tested with large and small samples, how GxE research can be carried out before as well as after replicated gene discovery, the uses of GxE research as a tool for gene discovery, the importance of construct validation in evaluating GxE research, and the contribution of GxE research to the public understanding of genetic science.
Response to antidepressants is interindividually variable. It has been suggested that this variability is a direct consequence of etiological heterogeneity. Therefore, the same genes, environments, ...and gene–environment interactions implicated in different etiological pathways to depression may also predict response to treatment. This article reviews the evidence relevant to this hypothesis by first outlining the roles of genes, environments, and gene–environment interplay in the etiology of depression, and then considering the same factors in treatment response. Environmental exposures, such as childhood maltreatment, are potent predictors of both depression and treatment response. Although alone genetic factors have failed to consistently predict either phenotype, several polymorphisms have been shown to moderate the effects of environmental adversity on the development of depression and treatment response. These findings suggest that the dissection of etiological pathways to depression may provide the key to understanding and predicting response to antidepressants.
In general, mothers with depression experience more environmental and family risk factors, and lead riskier lifestyles, than mothers who are not depressed.
To test whether the exposure of a child to ...risk factors associated with mental health adds to the prediction of child psychopathology beyond exposure to maternal depression.
In 7429 mother-offspring pairs participating in the Avon Longitudinal Study of Parents and Children in the UK, maternal depression was assessed when the children were aged 1.5 years; multiple risk factor exposures were examined between birth and 2 years of age; and DSM-IV-based externalising and internalising diagnoses were evaluated when the children were 7.5 years of age.
Children of clinically depressed mothers were exposed to more risk factors associated with maternal mental health. Maternal depression increased diagnoses of externalising and internalising disorders, but a substantial portion of these associations was explained by increased risk factor exposure (41% for externalising and 37% for internalising disorders). At the same time, these risk exposures significantly increased the odds of both externalising and internalising diagnoses, over and above the influence of maternal depression.
Children of clinically depressed mothers are exposed to both maternal psychopathology and risks that are associated with maternal mental health. These results may explain why treating mothers with depression shows beneficial effects for children, but does not completely neutralise the increased risk of psychopathology and impairment.
Phenotypic misclassification (between cases) has been shown to reduce the power to detect association in genetic studies. However, it is conceivable that complex traits are heterogeneous with respect ...to individual genetic susceptibility and disease pathophysiology, and that the effect of heterogeneity has a larger magnitude than the effect of phenotyping errors. Although an intuitively clear concept, the effect of heterogeneity on genetic studies of common diseases has received little attention. Here we investigate the impact of phenotypic and genetic heterogeneity on the statistical power of genome wide association studies (GWAS). We first performed a study of simulated genotypic and phenotypic data. Next, we analyzed the Wellcome Trust Case-Control Consortium (WTCCC) data for diabetes mellitus (DM) type 1 (T1D) and type 2 (T2D), using varying proportions of each type of diabetes in order to examine the impact of heterogeneity on the strength and statistical significance of association previously found in the WTCCC data. In both simulated and real data, heterogeneity (presence of "non-cases") reduced the statistical power to detect genetic association and greatly decreased the estimates of risk attributed to genetic variation. This finding was also supported by the analysis of loci validated in subsequent large-scale meta-analyses. For example, heterogeneity of 50% increases the required sample size by approximately three times. These results suggest that accurate phenotype delineation may be more important for detecting true genetic associations than increase in sample size.
Abstract
Background
The greater presence of neurodevelopmental antecedants may differentiate schizophrenia from bipolar disorders (BD). Machine learning/pattern recognition allows us to estimate the ...biological age of the brain from structural magnetic resonance imaging scans (MRI). The discrepancy between brain and chronological age could contribute to early detection and differentiation of BD and schizophrenia.
Methods
We estimated brain age in 2 studies focusing on early stages of schizophrenia or BD. In the first study, we recruited 43 participants with first episode of schizophrenia-spectrum disorders (FES) and 43 controls. In the second study, we included 96 offspring of bipolar parents (48 unaffected, 48 affected) and 60 controls. We used relevance vector regression trained on an independent sample of 504 controls to estimate the brain age of study participants from structural MRI. We calculated the brain-age gap estimate (BrainAGE) score by subtracting the chronological age from the brain age.
Results
Participants with FES had higher BrainAGE scores than controls (F(1, 83) = 8.79, corrected P = .008, Cohen’s d = 0.64). Their brain age was on average 2.64 ± 4.15 years greater than their chronological age (matched t(42) = 4.36, P < .001). In contrast, participants at risk or in the early stages of BD showed comparable BrainAGE scores to controls (F(2,149) = 1.04, corrected P = .70, η2 = 0.01) and comparable brain and chronological age.
Conclusions
Early stages of schizophrenia, but not early stages of BD, were associated with advanced BrainAGE scores. Participants with FES showed neurostructural alterations, which made their brains appear 2.64 years older than their chronological age. BrainAGE scores could aid in early differential diagnosis between BD and schizophrenia.