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Background: The coronavirus disease 2019 (COVID-19) pandemic and mitigation measures are likely to have a marked effect on mental health. It is important to use longitudinal data to improve inferences. Aims: To quantify the prevalence of depression, anxiety and mental wellbeing before and during the COVID-19 pandemic. To identify groups at risk of depression and/or anxiety during the pandemic. Methods: Data were from two generations of the Avon Longitudinal Study of Parents and Children (ALSPAC): the index generation (ALSPAC-young, n=2850, mean age=28), parent's generation (ALSPAC-parents, n=3720, mean age=59), and Generation Scotland (GS, n=4233, mean age=59). Depression was measured using the Short Mood and Feelings Questionnaire (SMFQ) in ALSPAC and the Patient Health Questionnaire (PHQ-9) in GS. Anxiety and mental wellbeing were measured using the Generalised Anxiety Disorder Assessment (GAD-7) and the Short Warwick Edinburgh Mental Wellbeing Scale. Results: Depression during COVID-19 was similar to pre-pandemic levels in ALSPAC-young, but those experiencing anxiety almost doubled during COVID-19: 24% (95% CI: 23%, 26%) compared to pre-pandemic levels of 13% (95% CI: 12%, 14%). In both ALSPAC and Generation Scotland, anxiety and depression during COVID-19 was greater in younger members, in women, in those with preexisting mental/physical health conditions, and in individuals in socioeconomic adversity, even when controlling for pre-pandemic anxiety and depression. Conclusions: These results provide evidence for increased anxiety in young people that is coincident with the pandemic. Specific groups are at elevated risk of depression and anxiety during COVID-19. This is important for planning mental health provisions now and for long-term impact beyond this pandemic.

The frequency of, and risk factors for, long COVID are unclear among community-based individuals with a history of COVID-19. To elucidate the burden and possible causes of long COVID in the community, we coordinated analyses of survey data from 6907 individuals with self-reported COVID-19 from 10 UK longitudinal study (LS) samples and 1.1 million individuals with COVID-19 diagnostic codes in electronic healthcare records (EHR) collected by spring 2021. Proportions of presumed COVID-19 cases in LS reporting any symptoms for 12+ weeks ranged from 7.8% and 17% (with 1.2 to 4.8% reporting debilitating symptoms). Increasing age, female sex, white ethnicity, poor pre-pandemic general and mental health, overweight/obesity, and asthma were associated with prolonged symptoms in both LS and EHR data, but findings for other factors, such as cardio-metabolic parameters, were inconclusive.

Background Childhood maltreatment is associated with poor mental and physical health. However, the mechanisms of gene-environment correlations and the potential causal effects of childhood maltreatment on health are unknown. Using genetics, we aimed to delineate the sources of gene-environment correlation for childhood maltreatment and the causal relationship between childhood maltreatment and health. MethodsWe did a genome-wide association study meta-analysis of childhood maltreatment using data from the UK Biobank (n=143 473), Psychiatric Genomics Consortium (n=26 290), Avon Longitudinal Study of Parents and Children (n=8346), Adolescent Brain Cognitive Development Study (n=5400), and Generation R (n=1905). We included individuals who had phenotypic and genetic data available. We investigated single nucleotide polymorphism heritability and genetic correlations among different subtypes, operationalisations, and reports of childhood maltreatment. Family-based and population-based polygenic score analyses were done to elucidate gene-environment correlation mechanisms. We used genetic correlation and Mendelian randomisation analyses to identify shared genetics and test causal relationships between childhood maltreatment and mental and physical health conditions.Findings Our meta-analysis of genome-wide association studies (N=185 414) identified 14 independent loci associated with childhood maltreatment (13 novel). We identified high genetic overlap (genetic correlations 0•24-1•00) among different maltreatment operationalisations, subtypes, and reporting methods. Within-family analyses provided some support for active and reactive gene-environment correlation but did not show the absence of passive geneenvironment correlation. Robust Mendelian randomisation suggested a potential causal role of childhood maltreatment in depression (unidirectional), as well as both schizophrenia and ADHD (bidirectional), but not in physical health conditions (coronary artery disease, type 2 diabetes) or inflammation (C-reactive protein concentration).Interpretation Childhood maltreatment has a heritable component, with substantial genetic correlations among different operationalisations, subtypes, and retrospective and prospective reports of childhood maltreatment. Familybased analyses point to a role of active and reactive gene-environment correlation, with equivocal support for passive correlation. Mendelian randomisation supports a (primarily bidirectional) causal role of childhood maltreatment on mental health, but not on physical health conditions. Our study identifies research avenues to inform the prevention of childhood maltreatment and its long-term effects.

Depression is a common mental illness and research has focused on late childhood and adolescence in an attempt to prevent or reduce later psychopathology and/or social impairments. It is important to establish and study population-averaged trajectories of depressive symptoms across adolescence as this could characterise specific changes in populations and help identify critical points to intervene with treatment. Multilevel growth-curve models were used to explore adolescent trajectories of depressive symptoms in 9301 individuals (57% female) from the Avon Longitudinal Study of Parents and Children, a UK based pregnancy cohort. Trajectories of depressive symptoms were constructed for males and females using the short mood and feelings questionnaire over 8 occasions, between 10 and 22 years old. Critical points of development such as age of peak velocity for depressive symptoms (the age at which depressive symptoms increase most rapidly) and the age of maximum depressive symptoms were also derived. The results suggested that from similar initial levels of depressive symptoms at age 11, females on average experienced steeper increases in depressive symptoms than males over their teenage and adolescent years until around the age of 20 when levels of depressive symptoms plateaued and started to decrease for both sexes. Females on average also had an earlier age of peak velocity of depressive symptoms that occurred at 13.5 years, compared to males who on average had an age of peak velocity at 16 years old. Evidence was less clear for a difference between the ages of maximum depressive symptoms which were on average 19.6 years for females and 20.4 for males. Identifying critical periods for different population subgroups may provide useful knowledge for treating and preventing depression and could be tailored to be time specific for certain groups. Possible explanations and recommendations are discussed.

Background: The impact of COVID-19 on mental health is unclear. Evidence from longitudinal studies with pre pandemic data are needed to address (1) how mental health has changed from pre-pandemic levels to during the COVID-19 pandemic and (2), whether there are groups at greater risk of poorer mental health during the pandemic? Methods: We used data from COVID-19 surveys (completed through April/May 2020), nested within two large longitudinal population cohorts with harmonised measures of mental health: two generations of the Avon Longitudinal Study of Parents and Children (ALPSAC): the index generation ALSPAC-G1 (n= 2850, mean age 28) and the parents generation ALSPAC-G0 (n= 3720, mean age = 59) and Generation Scotland: Scottish Family Health Study (GS, (n= 4233, mean age = 59), both with validated pre-pandemic measures of mental health and baseline factors. To answer question 1, we used ALSPAC-G1, which has identical mental health measures before and during the pandemic. Question 2 was addressed using both studies, using pre-pandemic and COVID-19 specific factors to explore associations with depression and anxiety in COVID-19. Findings: In ALSPAC-G1 there was evidence that anxiety and lower wellbeing, but not depression, had increased in COVID-19 from pre-pandemic assessments. The percentage of individuals with probable anxiety disorder was almost double during COVID-19: 24% (95% CI 23%, 26%) compared to pre-pandemic levels (13%, 95% CI 12%, 14%), with clinically relevant effect sizes. In both ALSPAC and GS, depression and anxiety were greater in younger populations, women, those with pre-existing mental and physical health conditions, those living alone and in socio-economic adversity. We did not detect evidence for elevated risk in key workers or health care workers. Interpretation: These results suggest increases in anxiety and lower wellbeing that may be related to the COVID-19 pandemic and/or its management, particularly in young people. This research highlights that specific groups may be disproportionally at risk of elevated levels of depression and anxiety during COVID-19 and supports recent calls for increasing funds for mental health services. Funding: The UK Medical Research Council (MRC), the Wellcome Trust and University of Bristol.

IMPORTANCE Less favorable trajectories of depressive mood from adolescence to early adulthood are associated with current and later psychopathology, impaired educational attainment, and social dysfunction, yet the genetic and environmental risk factors associated with these trajectories are not fully established. Examining what risk factors are associated with different trajectories of depressive mood could help identify the nature of depression symptoms and improve preventive interventions for those at most risk. OBJECTIVE To examine the differential associations of genetic and environmental risk factors with trajectories of depression symptoms among individuals observed from ages 10 to 24 years. DESIGN, SETTING, AND PARTICIPANTS In a longitudinal cohort study established in 1990 and currently ongoing (the Avon Longitudinal Study of Parents and Children [ALSPAC]), growth mixture modeling was used to identify trajectories of depression symptoms in 9394 individuals in the United Kingdom. Associations of different risk factors with these trajectories were then examined. Analysis was conducted between August 2018 and January 2019. MAIN OUTCOMES AND MEASURES Trajectories were composed from depression symptoms measured using the Short Mood and Feelings Questionnaire at 9 occasions from ages 10 to 24 years. Risk factors included sex, a polygenic risk score taken from a recent genome-wide association study of depression symptoms, maternal postnatal depression, partner cruelty to the offspring's mother when the child was aged 2 to 4 years, childhood anxiety at age 8 years, and being bullied at age 10 years. RESULTS Data on all risk factors, confounders, and the outcome were available for 3525 individuals, including 1771 (50.2%) who were female. Trajectories were assessed between the mean (SD) age of 10.7 (0.3) years and mean (SD) age of 23.8 (0.5) years. Overall, 5 distinct trajectories of depression symptoms were identified: (1) stable low (2506 individuals [71.1%]), (2) adolescent limited (325 individuals [9.2%]), (3) childhood limited (203 individuals [5.8%]), (4) early-adult onset (393 individuals [11.1%]), and (5) childhood persistent (98 individuals [2.8%]). Of all the associations of risk factors with trajectories, sex (odds ratio [OR], 6.45; 95% CI, 2.89-14.38), the polygenic risk score for depression symptoms (OR, 1.47; 95% CI, 1.10-1.96), and childhood anxiety (OR, 1.30; 95% CI, 1.16-1.45) showed the strongest association with the childhood-persistent trajectory of depression symptoms compared with the stable-low trajectory. Maternal postnatal depression (OR, 2.39; 95% CI, 1.41-4.07) had the strongest association with the early-adult-onset trajectory, while partner (continued) Key Points Question Are genetic and environmental risk factors associated with different trajectories of depression symptoms during adolescence and young adulthood? Findings In a cohort study of 3525 individuals observed from ages 10 to 24 years, both genetic and environmental risk factors were associated with childhood-persistent and ear...

The impact of long COVID is increasingly recognised, but risk factors are poorly characterised. We analysed questionnaire data on symptom duration from 10 longitudinal study (LS) samples and electronic healthcare records (EHR) to investigate sociodemographic and health risk factors associated with long COVID, as part of the UK National Core Study for Longitudinal Health and Wellbeing.MethodsAnalysis was conducted on 6,899 adults self-reporting COVID-19 from 45,096 participants of the UK LS, and on 3,327 cases assigned a long COVID code in primary care EHR out of 1,199,812 adults diagnosed with acute COVID-19. In LS, we derived two outcomes: symptoms lasting 4+ weeks and symptoms lasting 12+ weeks. Associations of potential risk factors (age, sex, ethnicity, socioeconomic factors, smoking, general and mental health, overweight/obesity, diabetes, hypertension, hypercholesterolaemia, and asthma) with these two outcomes were assessed, using logistic regression, with meta-analyses of findings presented alongside equivalent results from EHR analyses.ResultsFunctionally limiting long COVID for 12+ weeks affected between 1.2% (age 20), and 4.8% (age 63) of people reporting COVID-19 in LS. The proportion reporting symptoms overall for 12+ weeks ranged from 7.8 (mean age 28) to 17% (mean age 58) and for 4+ weeks 4.2% (age 20) to 33.1% (age 56). Age was associated with a linear increase in long COVID between age 20-70. Being female (LS: OR=1.49; 95%CI:1.24-1.79; EHR: OR=1.51 [1.41-1.61]), poor pre-pandemic mental health (LS: OR=1.46 [1.17-1.83]; EHR: OR=1.57 [1.47-1.68]) and poor general health (LS: OR=1.62 [1.25-2.09]; EHR: OR=1.26; [1.18-1.35]) were associated with higher risk of long COVID. Individuals with asthma also had higher risk (LS: OR=1.32 [1.07-1.62]; EHR: OR=1.56 [1.46-1.67]), as did those categorised as overweight or obese (LS: OR=1.25 [1.01-1.55]; EHR: OR=1.31 [1.21-1.42]) though associations for symptoms lasting 12+ weeks were less pronounced. Non-white ethnic minority groups had lower 4+ week symptom risk (LS: OR=0.32 [0.22-0.47]), a finding consistent in EHR. Associations were not observed for other risk factors. Few participants in the studies had been admitted to hospital (0.8-5.2%).ConclusionsLong COVID is clearly distributed differentially according to several sociodemographic and pre-existing health factors. Establishing which of these risk factors are causal and predisposing is necessary to further inform strategies for preventing and treating long COVID.