In order to deal with disastrous situations needing massive healthcare support, a new tool, financed by FEDER European funds (Interreg POCTEFA program) has been designed: the multipurpose mobile hospital Europe Occitanie (UMPEO). It is a projectable, foldable, versatile and autonomous truck with an interchangeable function from advanced medical post to operational command center, for acute events involving mass gathering or during multiple victims disasters. This study aims to show the usefulness of this structure during the COVID-19 health crisis.

The UMPEO is a shelter deployable in an emergency ward or intensive care unit, mobilizable in one hour, projectable by truck and autonomous for the first two hours. A descriptive, transversal, European study was carried out to describe its use in the cross-border countries of the Pyrenees (France, Spain and Andorra). When applicable, demographic data were gathered and/or a satisfaction questionnaire was given to the caregivers involved.

Between September 8, 2020 andFebruary 25, 2021, UMPEO was mobilized as a COVID-19 testing center, emergency department, vaccination center or as a command center at a political summit. Thus, 1322 screening tests were carried out over the screening three weeks deployment and 91% of the volunteers considered the screening operation useful. Used as a hospitalization ward, UMPEO was able to accommodate 266 patients over a period of four weeks. Eight hundred people were able to benefit from two doses of vaccines during the six weeks of the mobile vaccination campaign.

This tool, initially designed to be used in the event of a catastrophic event of an accidental or terrorist type or as a help station during mass gathering, has been diverted without any modification of its structure to meet the challenges of the global health crisis and provide a solution adapted to the population of countries bordering the Pyrenees.

Reward processing has been proposed to underpin the atypical social feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social reward processing in ASD.

Utilising a large sample, we aimed to assess reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD.

Functional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6–30.6 years of age) and 181 typically developing participants (7.6–30.8 years of age).

Across social and monetary reward anticipation, whole-brain analyses showed hypoactivation of the right ventral striatum in participants with ASD compared with typically developing participants. Further, region of interest analysis across both reward types yielded ASD-related hypoactivation in both the left and right ventral striatum. Across delivery of social and monetary reward, hyperactivation of the ventral striatum in individuals with ASD did not survive correction for multiple comparisons. Dimensional analyses of autism and attention-deficit hyperactivity disorder (ADHD) scores were not significant. In categorical analyses, post hoc comparisons showed that ASD effects were most pronounced in participants with ASD without co-occurring ADHD.

Our results do not support current theories linking atypical social interaction in ASD to specific alterations in social reward processing. Instead, they point towards a generalised hypoactivity of ventral striatum in ASD during anticipation of both social and monetary rewards. We suggest this indicates attenuated reward seeking in ASD independent of social content and that elevated ADHD symptoms may attenuate altered reward seeking in ASD.

We aimed to understand which non-household activities increased infection odds and contributed greatest to SARS-CoV-2 infections following the lifting of public health restrictions in England and Wales.

We undertook multivariable logistic regressions assessing the contribution to infections of activities reported by adult Virus Watch Community Cohort Study participants. We calculated adjusted weighted population attributable fractions (aPAF) estimating which activity contributed greatest to infections.

Among 11 413 participants (493 infections), infection was associated with: leaving home for work (aOR 1.35 (1.11–1.64), aPAF 17%), public transport (aOR 1.27 (1.04–1.57), aPAF 12%), shopping once (aOR 1.83 (1.36–2.45)) vs. more than three times a week, indoor leisure (aOR 1.24 (1.02–1.51), aPAF 10%) and indoor hospitality (aOR 1.21 (0.98–1.48), aPAF 7%). We found no association for outdoor hospitality (1.14 (0.94–1.39), aPAF 5%) or outdoor leisure (1.14 (0.82–1.59), aPAF 1%).

Essential activities (work and public transport) carried the greatest risk and were the dominant contributors to infections. Non-essential indoor activities (hospitality and leisure) increased risk but contributed less. Outdoor activities carried no statistical risk and contributed to fewer infections. As countries aim to ‘live with COVID’, mitigating transmission in essential and indoor venues becomes increasingly relevant.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Electroconvulsive therapy (ECT) is one of the most effective treatments for treatment-resistant depression (TRD). However, due to response delay and cognitive impairment, ECT remains an imperfect treatment. Compared to ECT, repetitive transcranial magnetic stimulation (rTMS) is less effective at treating severe depression, but has the advantage of being quick, easy to use, and producing almost no side effects. In this study, our objective was to assess the priming effect of rTMS sessions before ECT on clinical response in patients with TRD.

In this multicenter, randomized, double-blind, sham-controlled trial, 56 patients with TRD were assigned to active or sham rTMS before ECT treatment. Five sessions of active/sham neuronavigated rTMS were administered over the left dorsolateral prefrontal cortex (20 Hz, 90% resting motor threshold, 20 2 s trains with 60-s intervals, 800 pulses/session) before ECT (which was active for all patients) started. Any relative improvements were then compared between both groups after five ECT sessions, in order to assess the early response to treatment.

After ECT, the active rTMS group exhibited a significantly greater relative improvement than the sham group [43.4% (28.6%) v. 25.4% (17.2%)]. The responder rate in the active group was at least three times higher. Cognitive complaints, which were assessed using the Cognitive Failures Questionnaire, were higher in the sham rTMS group compared to the active rTMS group, but this difference was not corroborated by cognitive tests.

rTMS could be used to enhance the efficacy of ECT in patients with TRD. ClinicalTrials.gov: NCT02830399.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Patients with psychiatric disorders are exposed to high risk of COVID-19 and increased mortality. In this study, we set out to assess the clinical features and outcomes of patients with current psychiatric disorders exposed to COVID-19.

This multi-center prospective study was conducted in 22 psychiatric wards dedicated to COVID-19 inpatients between 28 February and 30 May 2020. The main outcomes were the number of patients transferred to somatic care units, the number of deaths, and the number of patients developing a confusional state. The risk factors of confusional state and transfer to somatic care units were assessed by a multivariate logistic model. The risk of death was analyzed by a univariate analysis.

In total, 350 patients were included in the study. Overall, 24 (7%) were transferred to medicine units, 7 (2%) died, and 51 (15%) patients presented a confusional state. Severe respiratory symptoms predicted the transfer to a medicine unit [odds ratio (OR) 17.1; confidence interval (CI) 4.9–59.3]. Older age, an organic mental disorder, a confusional state, and severe respiratory symptoms predicted mortality in univariate analysis. Age >55 (OR 4.9; CI 2.1–11.4), an affective disorder (OR 4.1; CI 1.6–10.9), and severe respiratory symptoms (OR 4.6; CI 2.2–9.7) predicted a higher risk, whereas smoking (OR 0.3; CI 0.1–0.9) predicted a lower risk of a confusional state.

COVID-19 patients with severe psychiatric disorders have multiple somatic comorbidities and have a risk of developing a confusional state. These data underline the need for extreme caution given the risks of COVID-19 in patients hospitalized for psychiatric disorders.