The impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health is still being unravelled. It is important to identify which individuals are at greatest risk of worsening symptoms. This study aimed to examine changes in depression, anxiety and post-traumatic stress disorder (PTSD) symptoms using prospective and retrospective symptom change assessments, and to find and examine the effect of key risk factors.

Online questionnaires were administered to 34 465 individuals (aged 16 years or above) in April/May 2020 in the UK, recruited from existing cohorts or via social media. Around one-third (n = 12 718) of included participants had prior diagnoses of depression or anxiety and had completed pre-pandemic mental health assessments (between September 2018 and February 2020), allowing prospective investigation of symptom change.

Prospective symptom analyses showed small decreases in depression (PHQ-9: −0.43 points) and anxiety [generalised anxiety disorder scale – 7 items (GAD)-7: −0.33 points] and increases in PTSD (PCL-6: 0.22 points). Conversely, retrospective symptom analyses demonstrated significant large increases (PHQ-9: 2.40; GAD-7 = 1.97), with 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Across both prospective and retrospective measures of symptom change, worsening depression, anxiety and PTSD symptoms were associated with prior mental health diagnoses, female gender, young age and unemployed/student status.

We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias-related underestimation of prior symptom severity.

Anxiety disorders are highly prevalent with an early age of onset. Understanding the aetiology of disorder emergence and recovery is important for establishing preventative measures and optimising treatment. Experimental approaches can serve as a useful model for disorder and recovery relevant processes. One such model is fear conditioning. We conducted a remote fear conditioning paradigm in monozygotic and dizygotic twins to determine the degree and extent of overlap between genetic and environmental influences on fear acquisition and extinction.

In total, 1937 twins aged 22–25 years, including 538 complete pairs from the Twins Early Development Study took part in a fear conditioning experiment delivered remotely via the Fear Learning and Anxiety Response (FLARe) smartphone app. In the fear acquisition phase, participants were exposed to two neutral shape stimuli, one of which was repeatedly paired with a loud aversive noise, while the other was never paired with anything aversive. In the extinction phase, the shapes were repeatedly presented again, this time without the aversive noise. Outcomes were participant ratings of how much they expected the aversive noise to occur when they saw either shape, throughout each phase.

Twin analyses indicated a significant contribution of genetic effects to the initial acquisition and consolidation of fear, and the extinction of fear (15, 30 and 15%, respectively) with the remainder of variance due to the non-shared environment. Multivariate analyses revealed that the development of fear and fear extinction show moderate genetic overlap (genetic correlations 0.4–0.5).

Fear acquisition and extinction are heritable, and share some, but not all of the same genetic influences.

To determine whether age, gender and marital status are associated with prognosis for adults with depression who sought treatment in primary care.

Medline, Embase, PsycINFO and Cochrane Central were searched from inception to 1st December 2020 for randomised controlled trials (RCTs) of adults seeking treatment for depression from their general practitioners, that used the Revised Clinical Interview Schedule so that there was uniformity in the measurement of clinical prognostic factors, and that reported on age, gender and marital status. Individual participant data were gathered from all nine eligible RCTs (N = 4864). Two-stage random-effects meta-analyses were conducted to ascertain the independent association between: (i) age, (ii) gender and (iii) marital status, and depressive symptoms at 3–4, 6–8,<Vinod: Please carry out the deletion of serial commas throughout the article> and 9–12 months post-baseline and remission at 3–4 months. Risk of bias was evaluated using QUIPS and quality was assessed using GRADE. PROSPERO registration: CRD42019129512. Pre-registered protocol https://osf.io/e5zup/.

There was no evidence of an association between age and prognosis before or after adjusting for depressive ‘disorder characteristics’ that are associated with prognosis (symptom severity, durations of depression and anxiety, comorbid panic disorderand a history of antidepressant treatment). Difference in mean depressive symptom score at 3–4 months post-baseline per-5-year increase in age = 0(95% CI: −0.02 to 0.02). There was no evidence for a difference in prognoses for men and women at 3–4 months or 9–12 months post-baseline, but men had worse prognoses at 6–8 months (percentage difference in depressive symptoms for men compared to women: 15.08% (95% CI: 4.82 to 26.35)). However, this was largely driven by a single study that contributed data at 6–8 months and not the other time points. Further, there was little evidence for an association after adjusting for depressive ‘disorder characteristics’ and employment status (12.23% (−1.69 to 28.12)). Participants that were either single (percentage difference in depressive symptoms for single participants: 9.25% (95% CI: 2.78 to 16.13) or no longer married (8.02% (95% CI: 1.31 to 15.18)) had worse prognoses than those that were married, even after adjusting for depressive ‘disorder characteristics’ and all available confounders.

Clinicians and researchers will continue to routinely record age and gender, but despite their importance for incidence and prevalence of depression, they appear to offer little information regarding prognosis. Patients that are single or no longer married may be expected to have slightly worse prognoses than those that are married. Ensuring this is recorded routinely alongside depressive ‘disorder characteristics’ in clinic may be important.

This study aimed to develop, validate and compare the performance of models predicting post-treatment outcomes for depressed adults based on pre-treatment data.

Individual patient data from all six eligible randomised controlled trials were used to develop (k = 3, n = 1722) and test (k = 3, n = 918) nine models. Predictors included depressive and anxiety symptoms, social support, life events and alcohol use. Weighted sum scores were developed using coefficient weights derived from network centrality statistics (models 1–3) and factor loadings from a confirmatory factor analysis (model 4). Unweighted sum score models were tested using elastic net regularised (ENR) and ordinary least squares (OLS) regression (models 5 and 6). Individual items were then included in ENR and OLS (models 7 and 8). All models were compared to one another and to a null model (mean post-baseline Beck Depression Inventory Second Edition (BDI-II) score in the training data: model 9). Primary outcome: BDI-II scores at 3–4 months.

Models 1–7 all outperformed the null model and model 8. Model performance was very similar across models 1–6, meaning that differential weights applied to the baseline sum scores had little impact.

Any of the modelling techniques (models 1–7) could be used to inform prognostic predictions for depressed adults with differences in the proportions of patients reaching remission based on the predicted severity of depressive symptoms post-treatment. However, the majority of variance in prognosis remained unexplained. It may be necessary to include a broader range of biopsychosocial variables to better adjudicate between competing models, and to derive models with greater clinical utility for treatment-seeking adults with depression.

Associations between parenting and child outcomes are often interpreted as reflecting causal, social influences. However, such associations may be confounded by genes common to children and their biological parents. To the extent that these shared genes influence behaviours in both generations, a passive genetic mechanism may explain links between them. Here we aim to quantify the relative importance of passive genetic v. social mechanisms in the intergenerational association between parent–offspring relationship quality and offspring internalizing problems in adolescence.

We used a Children-of-Twins (CoT) design with data from the parent-based Twin and Offspring Study of Sweden (TOSS) sample [909 adult twin pairs and their offspring; offspring mean age 15.75 (2.42) years], and the child-based Swedish Twin Study of CHild and Adolescent Development (TCHAD) sample [1120 adolescent twin pairs; mean age 13.67 (0.47) years]. A composite of parent-report measures (closeness, conflict, disagreements, expressions of affection) indexed parent–offspring relationship quality in TOSS, and offspring self-reported internalizing symptoms were assessed using the Child Behavior Checklist (CBCL) in both samples.

A social transmission mechanism explained the intergenerational association [r = 0.21 (0.16–0.25)] in our best-fitting model. A passive genetic transmission pathway was not found to be significant, indicating that parental genetic influences on parent–offspring relationship quality and offspring genetic influences on their internalizing problems were non-overlapping.

These results indicate that this intergenerational association is a product of social interactions between children and parents, within which bidirectional effects are highly plausible. Results from genetically informative studies of parenting-related effects should be used to help refine early parenting interventions aimed at reducing risk for psychopathology.

Maladaptive cognitive biases such as negative attributional style and hopelessness have been implicated in the development and maintenance of depression. According to the hopelessness theory of depression, hopelessness mediates the association between attributional style and depression. The aetiological processes underpinning this influential theory remain unknown. The current study investigated genetic and environmental influences on hopelessness and its concurrent and longitudinal associations with attributional style and depression across adolescence and emerging adulthood. Furthermore, given high co-morbidity between depression and anxiety, the study investigated whether these maladaptive cognitions constitute transdiagnostic cognitive content common to both internalizing symptoms.

A total of 2619 twins/siblings reported attributional style (mean age 15 and 17 years), hopelessness (mean age 17 years), and depression and anxiety symptoms (mean age 17 and 20 years).

Partial correlations revealed that attributional style and hopelessness were uniquely associated with depression but not anxiety symptoms. Hopelessness partially mediated the relationship between attributional style and depression. Hopelessness was moderately heritable (A = 0.37, 95% confidence interval 0.28–0.47), with remaining variance accounted for by non-shared environmental influences. Independent pathway models indicated that a set of common genetic influences largely accounted for the association between attributional style, hopelessness and depression symptoms, both concurrently and across development.

The results provide novel evidence that associations between attributional style, hopelessness and depression symptoms are largely due to shared genetic liability, suggesting developmentally stable biological pathways underpinning the hopelessness theory of depression. Both attributional style and hopelessness constituted unique cognitive content in depression. The results inform molecular genetics research and cognitive treatment approaches.

Depression and anxiety persist within and across diagnostic boundaries. The manner in which common v. disorder-specific genetic and environmental influences operate across development to maintain internalizing disorders and their co-morbidity is unclear. This paper investigates the stability and change of etiological influences on depression, panic, generalized, separation and social anxiety symptoms, and their co-occurrence, across adolescence and young adulthood.

A total of 2619 twins/siblings prospectively reported symptoms of depression and anxiety at mean ages 15, 17 and 20 years.

Each symptom scale showed a similar pattern of moderate continuity across development, largely underpinned by genetic stability. New genetic influences contributing to change in the developmental course of the symptoms emerged at each time point. All symptom scales correlated moderately with one another over time. Genetic influences, both stable and time-specific, overlapped considerably between the scales. Non-shared environmental influences were largely time- and symptom-specific, but some contributed moderately to the stability of depression and anxiety symptom scales. These stable, longitudinal environmental influences were highly correlated between the symptoms.

The results highlight both stable and dynamic etiology of depression and anxiety symptom scales. They provide preliminary evidence that stable as well as newly emerging genes contribute to the co-morbidity between depression and anxiety across adolescence and young adulthood. Conversely, environmental influences are largely time-specific and contribute to change in symptoms over time. The results inform molecular genetics research and transdiagnostic treatment and prevention approaches.

Parental depressive symptoms are associated with emotional and behavioural problems in offspring. However, genetically informative studies are needed to distinguish potential causal effects from genetic confounds, and longitudinal studies are required to distinguish parent-to-child effects from child-to-parent effects.

We conducted cross-sectional analyses on a sample of Swedish twins and their adolescent offspring (n = 876 twin families), and longitudinal analyses on a US sample of children adopted at birth, their adoptive parents, and their birth mothers (n = 361 adoptive families). Depressive symptoms were measured in parents, and externalizing and internalizing problems measured in offspring. Structural equation models were fitted to the data.

Results of model fitting suggest that associations between parental depressive symptoms and offspring internalizing and externalizing problems remain after accounting for genes shared between parent and child. Genetic transmission was not evident in the twin study but was evident in the adoption study. In the longitudinal adoption study child-to-parent effects were evident.

We interpret the results as demonstrating that associations between parental depressive symptoms and offspring emotional and behavioural problems are not solely attributable to shared genes, and that bidirectional effects may be present in intergenerational associations.

Little is known about the factors influencing the stability of obsessive–compulsive behaviour (OCB) from childhood to adolescence. The current study aimed to investigate: (1) the stability of paediatric OCB over a 12-year period; (2) the extent to which genetic and environmental factors influence stability; and (3) the extent to which these influences are stable or dynamic across development.

The sample included 14 743 twins from a population-based study. Parental ratings of severity of OCB were collected at ages 4, 7, 9 and 16 years.

OCB was found to be moderately stable over time. The genetic influence on OCB at each age was moderate, with significant effects also of non-shared environment. Genetic factors exerted a substantial influence on OCB persistence, explaining 59–80% of the stability over time. The results indicated genetic continuity, whereby genetic influences at each age continue to affect the expression of OCB at subsequent ages. However, we also found evidence for genetic attenuation in that genetic influences at one age decline in their influence over time, and genetic innovation whereby new genes ‘come on line’ at each age. Non-shared environment influenced stability of OCB to a lesser extent and effects were largely unique to each age and displayed negligible influences on OCB at later time points.

OCB appears to be moderately stable across development, and stability is largely driven by genetic factors. However, the genetic effects are not entirely constant, but rather the genetic influence on OCB appears to be a developmentally dynamic process.

The classification of anxiety and depressive disorders has long been debated and has important clinical implications. The present study combined a genetically sensitive design and multiple time points to investigate cognitive content specificity in anxiety and depressive disorder symptoms across anxiety sensitivity dimensions, a cognitive distortion implicated in both disorders.

Phenotypic and genetic correlations between anxiety sensitivity dimensions, anxiety and depressive disorder symptoms were examined at five waves of data collection within childhood, adolescence and early adulthood in two representative twin studies (n pairs = 300 and 1372).

The physical concerns dimension of anxiety sensitivity (fear of bodily symptoms) was significantly associated with anxiety but not depression at all waves. Genetic influences on physical concerns overlapped substantially more with anxiety than depression. Conversely, mental concerns (worry regarding cognitive control) were phenotypically more strongly associated with depression than anxiety. Social concerns (fear of publicly observable symptoms of anxiety) were associated with both anxiety and depression in adolescence. Genetic influences on mental and social concerns were shared to a similar extent with both anxiety and depression.

Phenotypic patterns of cognitive specificity and broader genetic associations between anxiety sensitivity dimensions, anxiety and depressive disorder symptoms were similar at all waves. Both disorder-specific and shared cognitive concerns were identified, suggesting it is appropriate to classify anxiety and depression as distinct but related disorders and confirming the clinical perspective that cognitive therapy is most likely to benefit by targeting cognitive concerns relating specifically to the individual's presenting symptoms across development.

Depression is commonly co-morbid with obsessive–compulsive disorder (OCD). However, it is unknown whether depression is a functional consequence of OCD or whether these disorders share a common genetic aetiology. This longitudinal twin study compared these two hypotheses.

Data were drawn from a longitudinal sample of adolescent twins and siblings (n = 2651; Genesis 12–19 study) and from a cross-sectional sample of adult twins (n = 4920). The longitudinal phenotypic associations between OCD symptoms (OCS) and depressive symptoms were examined using a cross-lag model. Multivariate twin analyses were performed to explore the genetic and environmental contributions to the cross-sectional and longitudinal relationship between OCS and depressive symptoms.

In the longitudinal phenotypic analyses, OCS at time 1 (wave 2 of the Genesis 12–19 study) predicted depressive symptoms at time 2 (wave 3 of the Genesis 12–19 study) to a similar extent to which depressive symptoms at time 1 predicted OCS at time 2. Cross-sectional twin analyses in both samples indicated that common genetic factors explained 52–65% of the phenotypic correlation between OCS and depressive symptoms. The proportion of the phenotypic correlation due to common non-shared environmental factors was considerably smaller (35%). In the adolescent sample, the longitudinal association between OCS at time 1 and subsequent depressive symptoms was accounted for by the genetic association between OCS and depressive symptoms at time 1. There was no significant environmental association between OCS and later depressive symptoms.

The present findings show that OCS and depressive symptoms co-occur primarily due to shared genetic factors and suggest that genetic, rather than environmental, effects account for the longitudinal relationship between OCS and depressive symptoms.

Certain aspects of sleep co-occur with externalizing behaviours in youth, yet little is known about these associations in adults. The present study: (1) examines the associations between diurnal preference (morningness versus eveningness), sleep quality and externalizing behaviours; (2) explores the extent to which genetic and environmental influences are shared between or are unique to these phenotypes; (3) examines the extent to which genetic and environmental influences account for these associations.

Questionnaires assessing diurnal preference, sleep quality and externalizing behaviours were completed by 1556 young adult twins and siblings.

A preference for eveningness and poor sleep quality were associated with greater externalizing symptoms [r=0.28 (95% CI 0.23–0.33) and 0.34 (95% CI 0.28–0.39), respectively]. A total of 18% of the genetic influences on externalizing behaviours were shared with diurnal preference and sleep quality and an additional 14% were shared with sleep quality alone. Non-shared environmental influences common to the phenotypes were small (2%). The association between diurnal preference and externalizing behaviours was mostly explained by genetic influences [additive genetic influence (A)=80% (95% CI 0.56–1.01)], as was the association between sleep quality and externalizing behaviours [A=81% (95% CI 0.62–0.99)]. Non-shared environmental (E) influences accounted for the remaining variance for both associations [E=20% (95% CI −0.01 to 0.44) and 19% (95% CI 0.01–0.38), respectively].

A preference for eveningness and poor sleep quality are moderately associated with externalizing behaviours in young adults. There is a moderate amount of shared genetic influences between the phenotypes and genetic influences account for a large proportion of the association between sleep and externalizing behaviours. Further research could focus on identifying specific genetic polymorphisms common to both sleep and externalizing behaviours.

To investigate the extent to which three putative ‘environmental’ risk factors, maternal punitive discipline (MPD), paternal punitive discipline (PPD) and negative life events (NLEs), share genetic influences with, and moderate the heritability of, externalizing behavior.

The sample consisted of 2647 participants, aged 12–19 years, from the G1219 and G1219Twins longitudinal studies. Externalizing behavior was measured using the Youth Self-Report, MPD, PPD and exposure to NLEs were assessed using the Negative Sanctions Scale and the Life Event Scale for Adolescents respectively.

Genetic influences overlapped for externalizing behavior and each ‘environmental’ risk, indicating gene–environment correlation. When controlling for the gene–environment correlation, genetic variance decreased, and both shared and non-shared environmental influences increased, as a function of MPD. Genetic variance increased as a function of PPD, and for NLEs the only interaction effect was on the level of non-shared environment influence unique to externalizing behavior.

The magnitude of the influence of genetic risk on externalizing behavior is contextually dependent, even after controlling for gene–environment correlation.