Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls.

Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses).

For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent.

This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals.

Neuroticism is a risk factor for selected mental and physical illnesses and is inversely associated with intelligence. Intelligence appears to interact with neuroticism and mitigate its detrimental effects on physical health and mortality. However, the inter-relationships of neuroticism and intelligence for major depressive disorder (MDD) and psychological distress has not been well examined.

Associations and interactions between neuroticism and general intelligence (g) on MDD, self-reported depression, and psychological distress were examined in two population-based cohorts: Generation Scotland: Scottish Family Health Study (GS:SFHS, n = 19,200) and UK Biobank (n = 90,529). The Eysenck Personality Scale Short Form-Revised measured neuroticism and g was extracted from multiple cognitive ability tests in each cohort. Family structure was adjusted for in GS:SFHS.

Neuroticism was strongly associated with increased risk for depression and higher psychological distress in both samples. Although intelligence conferred no consistent independent effects on depression, it did increase the risk for depression across samples once neuroticism was adjusted for. Results suggest that higher intelligence may ameliorate the association between neuroticism and self-reported depression although no significant interaction was found for clinical MDD. Intelligence was inversely associated with psychological distress across cohorts. A small interaction was found across samples such that lower psychological distress associates with higher intelligence and lower neuroticism, although effect sizes were small.

From two large cohort studies, our findings suggest intelligence acts a protective factor in mitigating the effects of neuroticism on psychological distress. Intelligence does not confer protection against diagnosis of depression in those high in neuroticism.

For many years, the prevailing paradigm has stated that in each individual with schizophrenia (SZ) the genetic risk is due to a combination of many genetic variants, individually of small effect. Recent empirical data are prompting a re-evaluation of this polygenic, common disease–common variant (CDCV) model. Evidence includes a lack of the expected strong positive findings from genome-wide association studies and the concurrent discovery of many different mutations that individually strongly predispose to SZ and other psychiatric disorders. This has led some to adopt a mixed model wherein some cases are caused by polygenic mechanisms and some by single mutations. This model runs counter to a substantial body of theoretical literature that had supposedly conclusively rejected Mendelian inheritance with genetic heterogeneity. Here we ask how this discrepancy between theory and data arose and propose a rationalization of the recent evidence base.

In light of recent empirical findings, we reconsider the methods and conclusions of early theoretical analyses and the explicit assumptions underlying them.

We show that many of these assumptions can now be seen to be false and that the model of genetic heterogeneity is consistent with observed familial recurrence risks, endophenotype studies and other population-wide parameters.

We argue for a more biologically consilient mixed model that involves interactions between disease-causing and disease-modifying variants in each individual. We consider the implications of this model for moving SZ research beyond statistical associations to pathogenic mechanisms.