Mental health difficulties are often exacerbated during the perinatal period. Policy and guidelines are increasingly being used to enhance the quality of healthcare. We conducted a literature review of published research relating to pregnancy and breastfeeding in mental health policy.

Relevant terms were searched in Medline, CINAHL, APA PsycINFO and EMBASE for articles published in English from 1970 until 2020. Only papers that referenced policy, guidance, legislation or standards were included. While a systematic approach was used, the nature of the results necessitated a narrative review.

Initially, 262 papers were identified, 44 met the inclusion criteria. Reproductive health is given sparse consideration in research relating to mental health policy. Despite this, some key areas emerged. These included: the need for proactive preconception psychoeducation, proactive screening of mothers of infants and young children for perinatal mental health issues, enhanced prescribing practice for women of child-bearing age, enhanced monitoring during pregnancy, development of safe modification of coercive practices should they need to be employed in emergency circumstances and targeted measures to reduce substance misuse. Themes that arose relating to breastfeeding and bonding are also described.

Female reproductive health is often ignored in research relating to mental health policy, guidelines and standards. These tools need to be harnessed to promote good healthcare. Reproductive health should be included in the care plan of all mental health patients. These topics need to be integrated into existing relevant policies and not isolated to a separate policy.

Evidence suggests that the COVID-19 pandemic was accompanied by an increased exposure to risk factors for psychosis, such as psychological stress, substance use, social isolation and deprivation, as well as a potential direct biological impact of the COVID-19 infection on psychosis. However, the impact of the COVID-19 pandemic on the rates of first-episode psychosis (FEP) has not yet been examined.

The aims of the current study were to 1) establish the FEP incidence between March 2019 and March 2021 in an inner London catchment area; 2) compare FEP incidence rates for the first year of the COVID-19 pandemic (March 2020 – February 2021), with those for the year prior (March 2019 – February 2020).

We screened the clinical records of all individuals living in the London boroughs of Southwark and Lambeth who were referred to the early intervention in psychosis services before (from 1 March 2019 to 28 February 2020) and during (from 1 March 2020 to 28 February 2021) the COVID-19 pandemic. We used Office for National Statistics (ONS) data to estimate the risk populations stratified by sex and age group. We computed crude and sex-age standardised FEP incidence per 100,000 persons-year. We used Poisson regression to calculate the incidence rate ratio (IRR) before and during the COVID-19 pandemic and to examine the incidence variation by sociodemographic factors.

A total of 321 incident cases of FEP were identified during the COVID-19 pandemic accounting for a crude rate of 70.1 (95% CI 62.4 - 77.7) per 100,000 person-year. The crude rate for the year before was 47.5 (95% CI 41.2 - 53.8). The incidence variation between the two years accounted for an adjusted IRR of 1.46 (95% CI 1.23 – 1.76). The increased FEP rates were equally observed across the boroughs of Southwark and Lambeth and men and women. Individuals aged 20-24 (IRR 1.66; 95% CI 1.13 – 2.42) and those from the black ethnic group (IRR 1.61; 95% CI 1·24 – 2·09) showed the greatest incidence increases.

To the best of our knowledge, this is the first study establishing the variation in FEP incidence before and during the COVID-19 pandemic across all adult age groups. We provide the first evidence that the COVID-19 pandemic resulted in a 46% increase in the incidence of psychotic disorders in South London. The increase was higher for young individuals and ethnic minorities. This finding should inform public health research and demonstrates the need for adequate resources for mental health secondary services.

None Declared

Tobacco is a highly prevalent substance of abuse in patients with psychosis. Previous studies have reported an association between tobacco use and schizophrenia. The aim of this study was to analyze the relationship between tobacco use and first-episode psychosis (FEP), age at onset of psychosis, and specific diagnosis of psychosis.

The sample consisted of 1105 FEP patients and 1355 controls from the European Network of National Schizophrenia Networks Studying Gene–Environment Interactions (EU-GEI) study. We assessed substance use with the Tobacco and Alcohol Questionnaire and performed a series of regression analyses using case-control status, age of onset of psychosis, and diagnosis as outcomes and tobacco use and frequency of tobacco use as predictors. Analyses were adjusted for sociodemographic characteristics, alcohol, and cannabis use.

After controlling for cannabis use, FEP patients were 2.6 times more likely to use tobacco [p ⩽ 0.001; adjusted odds ratio (AOR) 2.6; 95% confidence interval (CI) [2.1–3.2]] and 1.7 times more likely to smoke 20 or more cigarettes a day (p = 0.003; AOR 1.7; 95% CI [1.2–2.4]) than controls. Tobacco use was associated with an earlier age at psychosis onset (β = −2.3; p ⩽ 0.001; 95% CI [−3.7 to −0.9]) and was 1.3 times more frequent in FEP patients with a diagnosis of schizophrenia than in other diagnoses of psychosis (AOR 1.3; 95% CI [1.0–1.8]); however, these results were no longer significant after controlling for cannabis use.

Tobacco and heavy-tobacco use are associated with increased odds of FEP. These findings further support the relevance of tobacco prevention in young populations.

Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.

We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.

Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.

An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

Anorexia nervosa (AN) is a psychiatric disorder associated with marked morbidity. Whilst AN genetic studies could identify novel treatment targets, integration of functional genomics data, including transcriptomics and proteomics, would assist to disentangle correlated signals and reveal causally associated genes.

We used models of genetically imputed expression and splicing from 14 tissues, leveraging mRNA, protein, and mRNA alternative splicing weights to identify genes, proteins, and transcripts, respectively, associated with AN risk. This was accomplished through transcriptome, proteome, and spliceosome-wide association studies, followed by conditional analysis and finemapping to prioritise candidate causal genes.

We uncovered 134 genes for which genetically predicted mRNA expression was associated with AN after multiple-testing correction, as well as four proteins and 16 alternatively spliced transcripts. Conditional analysis of these significantly associated genes on other proximal association signals resulted in 97 genes independently associated with AN. Moreover, probabilistic finemapping further refined these associations and prioritised putative causal genes. The gene WDR6, for which increased genetically predicted mRNA expression was correlated with AN, was strongly supported by both conditional analyses and finemapping. Pathway analysis of genes revealed by finemapping identified the pathway regulation of immune system process (overlapping genes = MST1, TREX1, PRKAR2A, PROS1) as statistically overrepresented.

We leveraged multiomic datasets to genetically prioritise novel risk genes for AN. Multiple-lines of evidence support that WDR6 is associated with AN, whilst other prioritised genes were enriched within immune related pathways, further supporting the role of the immune system in AN.

We summarize what we assess as the past year's most important findings within climate change research: limits to adaptation, vulnerability hotspots, new threats coming from the climate–health nexus, climate (im)mobility and security, sustainable practices for land use and finance, losses and damages, inclusive societal climate decisions and ways to overcome structural barriers to accelerate mitigation and limit global warming to below 2°C.

We synthesize 10 topics within climate research where there have been significant advances or emerging scientific consensus since January 2021. The selection of these insights was based on input from an international open call with broad disciplinary scope. Findings concern: (1) new aspects of soft and hard limits to adaptation; (2) the emergence of regional vulnerability hotspots from climate impacts and human vulnerability; (3) new threats on the climate–health horizon – some involving plants and animals; (4) climate (im)mobility and the need for anticipatory action; (5) security and climate; (6) sustainable land management as a prerequisite to land-based solutions; (7) sustainable finance practices in the private sector and the need for political guidance; (8) the urgent planetary imperative for addressing losses and damages; (9) inclusive societal choices for climate-resilient development and (10) how to overcome barriers to accelerate mitigation and limit global warming to below 2°C.

Science has evidence on barriers to mitigation and how to overcome them to avoid limits to adaptation across multiple fields.

Gene x environment (G×E) interactions, i.e. genetic modulation of the sensitivity to environmental factors and/or environmental control of the gene expression, have not been reliably established regarding aetiology of psychotic disorders. Moreover, recent studies have shown associations between the polygenic risk scores for schizophrenia (PRS-SZ) and some risk factors of psychotic disorders, challenging the traditional gene v. environment dichotomy. In the present article, we studied the role of GxE interaction between psychosocial stressors (childhood trauma, stressful life-events, self-reported discrimination experiences and low social capital) and the PRS-SZ on subclinical psychosis in a population-based sample.

Data were drawn from the EUropean network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study, in which subjects without psychotic disorders were included in six countries. The sample was restricted to European descendant subjects (n = 706). Subclinical dimensions of psychosis (positive, negative, and depressive) were measured by the Community Assessment of Psychic Experiences (CAPE) scale. Associations between the PRS-SZ and the psychosocial stressors were tested. For each dimension, the interactions between genes and environment were assessed using linear models and comparing explained variances of ‘Genetic’ models (solely fitted with PRS-SZ), ‘Environmental’ models (solely fitted with each environmental stressor), ‘Independent’ models (with PRS-SZ and each environmental factor), and ‘Interaction’ models (Independent models plus an interaction term between the PRS-SZ and each environmental factor). Likelihood ration tests (LRT) compared the fit of the different models.

There were no genes-environment associations. PRS-SZ was associated with positive dimensions (β = 0.092, R2 = 7.50%), and most psychosocial stressors were associated with all three subclinical psychotic dimensions (except social capital and positive dimension). Concerning the positive dimension, Independent models fitted better than Environmental and Genetic models. No significant GxE interaction was observed for any dimension.

This study in subjects without psychotic disorders suggests that (i) the aetiological continuum hypothesis could concern particularly the positive dimension of subclinical psychosis, (ii) genetic and environmental factors have independent effects on the level of this positive dimension, (iii) and that interactions between genetic and individual environmental factors could not be identified in this sample.

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.

Of those with schizophrenia, one third develop treatment-resistant illness. Nearly 60% of these benefit from clozapine- the only antipsychotic medication licensed in this group.

As treatment-resistant illness developed in the follow-up of a first-episode psychosis (FEP) cohort, clozapine was prescribed. This study retrospectively compared the clozapine prescribing patterns, within this cohort, to National Institute for Health and Care Excellence (NICE) guidelines. In addition, impact on hospitalisation, physical health monitoring and augmentation strategies employed following clozapine initiation were examined. Factors delaying initiation of clozapine treatment or contributing to its discontinuation were also explored.

The study included 339 individuals resident within an Irish community mental health team catchment area, referred with FEP from 1 January 2005 to 31 August 2016. Data were extracted from electronic medical records.

Within the cohort, clozapine was prescribed to 32 individuals (9.4%). The mean number of adequate trials of antipsychotic prior to starting clozapine was 2.74 (SD 1.13; range 1–5). The mean time to clozapine trial was 2.1 years (SD 1.95; range 0.17–6.25). Following initiation of clozapine, mean hospital admissions per year fell from 2.3 to 0.3 (p=0.00). Mean inpatient days pre- and post-clozapine also decreased (147 vs. 53; p=0.00). In all, 18 patients ceased use of clozapine, 5 temporarily and 13 permanently.

Patients are being prescribed clozapine earlier than previously demonstrated. However, delayed treatment remains common, and many patients discontinue clozapine. Further research is necessary to describe and address factors which contribute to its discontinuation.

No significant relationships.

Child abuse is associated with a wide range of mental disease including psychotic disorders. Few studies have investigated the role of child abuse in contributing to increase the risk of psychosis in migrant population.

To explore the risk of first episode psychosis (FEP) in migrants and natives for each type of trauma i.e. physical abuse (P.A.), sexual abuse (S.A.), emotional abuse (E.A.), physical neglect (P.N.) and emotional neglect (E.N.).

Within a large case- control incidence sample of FEP from the EU-GEI study (The EUropean Network of National Schizophrenia Networks Studying Gene–Environment Interactions) we evalued the assocition of childhood trauma with FEP in migrants and natives. Associations were adjusted for age, gender, social status, level of education, family history of psychosis and cannabis use. Trauma was assessed through Childhood Trauma Questionnaire (CTQ).

CTQ mean score was higher in FEP migrants (45.4, sd 15.6) than in FEP natives (41.7, sd 13.9) (p = 0.002). In natives every type of child abuse was associated with FEP. In migrants P.A., S.A., P.N. were associated with FEP. We found a dose – dependent relationship between trauma and FEP.

Child abuse is common in individuals with psychosis. FEP migrants are more exposed to childhood trauma. Clinicians should routinely assess patients for childhood trauma. When treating a FEP migrant patient, clinicians must be aware of an underlying traumatic childhood adversity more than of a traumatic migration history.

Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are commonly reported co-occurring mental health consequences of psychological trauma exposure. The disorders have high genetic overlap. Trauma is a complex phenotype but research suggests that trauma sensitivity has a heritable basis. We investigated whether sensitivity to trauma in those with MDD reflects a similar genetic component in those with PTSD.

Genetic correlations between PTSD and MDD in individuals reporting trauma and MDD in individuals not reporting trauma were estimated, as well as with recurrent MDD and single-episode MDD, using genome-wide association study (GWAS) summary statistics. Genetic correlations were replicated using PTSD data from the Psychiatric Genomics Consortium and the Million Veteran Program. Polygenic risk scores were generated in UK Biobank participants who met the criteria for lifetime MDD (N = 29 471). We investigated whether genetic loading for PTSD was associated with reporting trauma in these individuals.

Genetic loading for PTSD was significantly associated with reporting trauma in individuals with MDD [OR 1.04 (95% CI 1.01–1.07), Empirical-p = 0.02]. PTSD was significantly more genetically correlated with recurrent MDD than with MDD in individuals not reporting trauma (rg differences = ~0.2, p < 0.008). Participants who had experienced recurrent MDD reported significantly higher rates of trauma than participants who had experienced single-episode MDD (χ2 > 166, p < 0.001)

Our findings point towards the existence of genetic variants associated with trauma sensitivity that might be shared between PTSD and MDD, although replication with better powered GWAS is needed. Our findings corroborate previous research highlighting trauma exposure as a key risk factor for recurrent MDD.