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The apparently large genetic contribution to the aetiology of mental illness presents a formidable puzzle. Unlike common physical disorders, mental illness usually has an onset early in the reproductive age and is associated with substantial reproductive disadvantage. Therefore, genetic variants associated with vulnerability to mental illness should be under strong negative selection pressure and be eliminated from the genetic pool through natural selection. Still, mental disorders are common and twin studies indicate a strong genetic contribution to their aetiology. Several theories have been advanced to explain the paradox of high heritability and reproductive disadvantage associated with the same common phenotype, but none provides a satisfactory explanation for all types of mental illness. At the same time, identification of the molecular substrate underlying the large genetic contribution to the aetiology of mental illness is proving more difficult than expected. The quest for genetic variants associated with vulnerability to mental illness is predicated upon the common disease/common variant (CDCV) hypothesis. On the basis of a summary of evidence, it is concluded that the CDCV hypothesis is untenable for most types of mental illness. An alternative evolution-informed framework is proposed, which suggests that gene–environment interactions and rare genetic variants constitute most of the genetic contribution to mental illness. Common mental illness with mild reproductive disadvantage is likely to have a large contribution from interactions between common genetic variants and environmental exposures. Severe mental illness that confers strong reproductive disadvantage is likely to have a large and pleiotropic contribution from rare variants of recent origin. This framework points to a need for a paradigm change in genetic research to enable major progress in elucidating the aetiology of mental illness.

An updated review of 34 human observational studies indicates that the length polymorphism of the serotonin transporter gene moderates the effect of environmental adversity in the development of depression. This finding depends on the use of contextual or objective methods to assess environmental adversity and is attenuated when self-report instruments are used. Inconsistent findings in male adolescents suggest a developmental stage and sex-specific protective mechanism. These systematic relationships between method and results should be followed up to specify causal mechanisms leading to depression.

In a number of human diseases, including depression, interactions between genetic and environmental factors have been identified in the absence of direct genotype-disorder associations. The lack of genes with major direct pathogenic effect suggests that genotype-specific vulnerabilities are balanced by adaptive advantages and implies aetiological heterogeneity. A model of depression is proposed that incorporates the interacting genetic and environmental factors over the life course and provides an explanatory framework for the heterogeneous aetiology of depression. Early environmental influences act on the genome to shape the adaptability to environmental changes in later life. The possibility is explored that genotype- and epigenotype-related traits can be harnessed to develop personalized therapeutic interventions. As diagnosis of depression alone is a weak predictor of response to specific treatments, aetiological subtypes can be used to inform the choice between treatments. As a specific application of this notion, a hypothesis is proposed regarding relative responsiveness of aetiological subtypes of depression to psychological treatment and antidepressant medication. Other testable predictions are likely to emerge from the general framework of interacting genetic, epigenetic and environmental mechanisms in depression.

Gene–environmental interaction (G × E) between a common functional polymorphism in the promoter region of the serotonin transporter gene ( 5-HTT) and environmental adversity on the onset of depression in humans has been found in fifteen independent studies. It is supported by evidence from animal experiments, pharmacological challenge and neuroimaging investigations. However, negative findings have been reported in two large samples. We explore reasons for the inconsistencies and suggest means to their resolution. Sample age and gender composition emerge as important factors. While the G × E has been consistently detected in young adult samples, there are contradictory findings in adolescent boys and elderly people. The method of assessment of environmental adversity is also important with detailed interview-based approaches being associated with positive G × E findings. Unresolved issues in the definition of the genotype include the dominance of alleles and influence of other polymorphisms, both in 5-HTT and other genes. Assessment of multiple adverse outcomes, including depression, substance use and self-destructive behaviour is needed to clarify the generalisability of the G × E pathogenic mechanisms. Biological and behavioural intermediate phenotypes are yet to be exploited to understand the mechanisms underlying the G × E.

Symptom dimensions have not yet been comprehensively tested as predictors of the substantial heterogeneity in outcomes of antidepressant treatment in major depressive disorder. We tested nine symptom dimensions derived from a previously published factor analysis of depression rating scales as predictors of outcome in 811 adults with moderate to severe depression treated with flexibly dosed escitalopram or nortriptyline in Genome-based Therapeutic Drugs for Depression (GENDEP). The effects of symptom dimensions were tested in mixed-effect regression models that controlled for overall initial depression severity, age, sex and recruitment centre. Significant results were tested for replicability in 3637 adult out-patients with non-psychotic major depression treated with citalopram in level I of Sequenced Treatment Alternatives to Relieve Depression (STAR*D). The interest-activity symptom dimension (reflecting low interest, reduced activity, indecisiveness and lack of enjoyment) at baseline strongly predicted poor treatment outcome in GENDEP, irrespective of overall depression severity, antidepressant type and outcome measure used. The prediction of poor treatment outcome by the interest-activity dimension was robustly replicated in STAR*D, independent of a comprehensive list of baseline covariates. Loss of interest, diminished activity and inability to make decisions predict poor outcome of antidepressant treatment even after adjustment for overall depression severity and other clinical covariates. The prominence of such symptoms may require additional treatment strategies and should be accounted for in future investigations of antidepressant response.

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. 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. 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. 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.

Larger grey matter volume of the inferior frontal gyrus (IFG) is among the most replicated biomarkers of genetic risk for bipolar disorders (BD). However, the IFG is a heterogeneous prefrontal region, and volumetric findings can be attributable to changes in cortical thickness (CT), surface area (SA) or gyrification. Here, we investigated the morphometry of IFG in participants at genetic risk for BD. We quantified the IFG cortical grey matter volume in 29 affected, 32 unaffected relatives of BD probands, and 42 controls. We then examined SA, CT, and cortical folding in subregions of the IFG. We found volumetric group differences in the right IFG, with the largest volumes in unaffected high-risk and smallest in control participants (F2,192 = 3.07, p = 0.01). The volume alterations were localized to the pars triangularis of the IFG (F2,97 = 4.05, p = 0.02), with no differences in pars opercularis or pars orbitalis. Pars triangularis volume was highly correlated with its SA [Pearson r(101) = 0.88, p < 0.001], which significantly differed between the groups (F2,97 = 4.45, p = 0.01). As with volume, the mean SA of the pars triangularis was greater in unaffected (corrected p = 0.02) and affected relatives (corrected p = 0.05) compared with controls. We did not find group differences in pars triangularis CT or gyrification. These findings strengthen prior knowledge about the volumetric findings in this region and provide a new insight into the localization and topology of IFG alterations. The unique nature of rIFG morphology in BD, with larger volume and SA early in the course of illness, could have practical implications for detection of participants at risk for BD.

Neuroimaging studies have demonstrated an association between lithium (Li) treatment and brain structure in human subjects. A crucial unresolved question is whether this association reflects direct neurochemical effects of Li or indirect effects secondary to treatment or prevention of episodes of bipolar disorder (BD). To address this knowledge gap, we compared manually traced hippocampal volumes in 37 BD patients with at least 2 years of Li treatment (Li group), 19 BD patients with <3 months of lifetime Li exposure over 2 years ago (non-Li group) and 50 healthy controls. All BD participants were followed prospectively and had at least 10 years of illness and a minimum of five episodes. We established illness course and long-term treatment response to Li using National Institute of Mental Health (NIMH) life charts. The non-Li group had smaller hippocampal volumes than the controls or the Li group (F 2,102 = 4.97, p = 0.009). However, the time spent in a mood episode on the current mood stabilizer was more than three times longer in the Li than in the non-Li group (t(51) = 2.00, p = 0.05). Even Li-treated patients with BD episodes while on Li had hippocampal volumes comparable to healthy controls and significantly larger than non-Li patients (t(43) = 2.62, corrected p = 0.02). Our findings support the neuroprotective effects of Li. The association between Li treatment and hippocampal volume seems to be independent of long-term treatment response and occurred even in subjects with episodes of BD while on Li. Consequently, these effects of Li on brain structure may generalize to patients with neuropsychiatric illnesses other than BD.

Response and remission defined by cut-off values on the last observed depression severity score are commonly used as outcome criteria in clinical trials, but ignore the time course of symptomatic change and may lead to inefficient analyses. We explore alternative categorization of outcome by naturally occurring trajectories of symptom change. Growth mixture models were applied to repeated measurements of depression severity in 807 participants with major depression treated for 12 weeks with escitalopram or nortriptyline in the part-randomized Genome-based Therapeutic Drugs for Depression study. Latent trajectory classes were validated as outcomes in drug efficacy comparison and pharmacogenetic analyses. The final two-piece growth mixture model categorized participants into a majority (75%) following a gradual improvement trajectory and the remainder following a trajectory with rapid initial improvement. The rapid improvement trajectory was over-represented among nortriptyline-treated participants and showed an antidepressant-specific pattern of pharmacogenetic associations. In contrast, conventional response and remission favoured escitalopram and produced chance results in pharmacogenetic analyses. Controlling for drop-out reduced drug differences on response and remission but did not affect latent trajectory results. Latent trajectory mixture models capture heterogeneity in the development of clinical response after the initiation of antidepressants and provide an outcome that is distinct from traditional endpoint measures. It differentiates between antidepressants with different modes of action and is robust against bias due to differential discontinuation.

Offspring of parents with major mood disorders (MDDs) are at increased risk for early psychopathology. We aim to compare the rates of neurodevelopmental disorders in offspring of parents with bipolar disorder, major depressive disorder, and controls. We established a lifetime diagnosis of neurodevelopmental disorders [attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disabilities, specific learning disorders, and motor disorders] using the Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime Version in 400 participants (mean age 11.3 + s.d. 3.9 years), including 93 offspring of parents with bipolar disorder, 182 offspring of parents with major depressive disorder, and 125 control offspring of parents with no mood disorder. Neurodevelopmental disorders were elevated in offspring of parents with bipolar disorder [odds ratio (OR) 2.34, 95% confidence interval (CI) 1.23-4.47, = 0.010] and major depressive disorder (OR 1.87, 95% CI 1.03-3.39, = 0.035) compared to controls. This difference was driven by the rates of ADHD, which were highest among offspring of parents with bipolar disorder (30.1%), intermediate in offspring of parents with major depressive disorder (24.2%), and lowest in controls (14.4%). There were no significant differences in frequencies of other neurodevelopmental disorders between the three groups. Chronic course of mood disorder in parents was associated with higher rates of any neurodevelopmental disorder and higher rates of ADHD in offspring. Our findings suggest monitoring for ADHD and other neurodevelopmental disorders in offspring of parents with MDDs may be indicated to improve early diagnosis and treatment.