Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Reaction time variability (RTV) has been estimated using Gaussian, ex-Gaussian, and diffusion model (DM) indices. Rarely have studies examined interrelationships among these performance indices in childhood, and the use of reaction time (RT) computational models has been slow to take hold in the developmental psychopathology literature. Here, we extend prior work in adults by examining the interrelationships among different model parameters in the ABCD sample and demonstrate how computational models of RT can clarify mechanisms of time-on-task effects and sex differences in RTs.

This study utilized trial-level data from the stop signal task from 8916 children (9–10 years old) to examine Gaussian, ex-Gaussian, and DM indicators of RTV. In addition to describing RTV patterns, we examined interrelations among these indicators, temporal patterns, and sex differences.

There was no one-to-one correspondence between DM and ex-Gaussian parameters. Nonetheless, drift rate was most strongly associated with standard deviation of RT and tau, while nondecisional processes were most strongly associated with RT, mu, and sigma. Performance worsened across time with changes driven primarily by decreasing drift rate. Boys were faster and less variable than girls, likely attributable to girls’ wide boundary separation.

Intercorrelations among model parameters are similar in children as has been observed in adults. Computational approaches play a crucial role in understanding performance changes over time and can also clarify mechanisms of group differences. For example, standard RT models may incorrectly suggest slowed processing speed in girls that is actually attributable to other factors.

Air dispersal of respiratory viruses other than SARS-CoV-2 has not been systematically reported. The incidence and factors associated with air dispersal of respiratory viruses are largely unknown.

We performed air sampling by collecting 72,000 L of air over 6 hours for pediatric and adolescent patients infected with parainfluenza virus 3 (PIF3), respiratory syncytial virus (RSV), rhinovirus, and adenovirus. The patients were singly or 2-patient cohort isolated in airborne infection isolation rooms (AIIRs) from December 3, 2021, to January 26, 2022. The viral load in nasopharyngeal aspirates (NPA) and air samples were measured. Factors associated with air dispersal were investigated and analyzed.

Of 20 singly isolated patients with median age of 30 months (range, 3 months–15 years), 7 (35%) had air dispersal of the viruses compatible with their NPA results. These included 4 (40%) of 10 PIF3-infected patients, 2 (66%) of 3 RSV-infected patients, and 1 (50%) of 2 adenovirus-infected patients. The mean viral load in their room air sample was 1.58×103 copies/mL. Compared with 13 patients (65%) without air dispersal, these 7 patients had a significantly higher mean viral load in their NPA specimens (6.15×107 copies/mL vs 1.61×105 copies/mL; P < .001). Another 14 patients were placed in cohorts as 7 pairs infected with the same virus (PIF3, 2 pairs; RSV, 3 pairs; rhinovirus, 1 pair; and adenovirus, 1 pair) in double-bed AIIRs, all of which had air dispersal. The mean room air viral load in 2-patient cohorts was significantly higher than in rooms of singly isolated patients (1.02×104 copies/mL vs 1.58×103 copies/mL; P = .020).

Air dispersal of common respiratory viruses may have infection prevention and public health implications.

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.

Psychosis is a major mental illness with first onset in young adults. The prognosis is poor in around half of the people affected, and difficult to predict. The few tools available to predict prognosis have major weaknesses which limit their use in clinical practice. We aimed to develop and validate a risk prediction model of symptom non-remission in first-episode psychosis.

Our development cohort consisted of 1027 patients with first-episode psychosis recruited between 2005 to 2010 from 14 early intervention services across the National Health Service in England. Our validation cohort consisted of 399 patients with first-episode psychosis recruited between 2006 to 2009 from a further 11 English early intervention services. The one-year non-remission rate was 52% and 54% in the development and validation cohorts, respectively. Multivariable logistic regression was used to develop a risk prediction model for non-remission, which was externally validated.

The prediction model showed good discrimination (C-statistic of 0.74 (0.72, 0.76) and adequate calibration with intercept alpha of 0.13 (0.03, 0.23) and slope beta of 0.99 (0.87, 1.12). Our model improved the net-benefit by 16% at a risk threshold of 50%, equivalent to 16 more detected non-remitted first-episode psychosis individuals per 100 without incorrectly classifying remitted cases.

Once prospectively validated, our first episode psychosis prediction model could help identify patients at increased risk of non-remission at initial clinical contact.

Telephone consultations have been in clinical use since the early 1960s and are increasing in frequency and importance in many areas of medicine. With the advent of the COVID-19 pandemic in 2020, the use of telemedicine consultations increased dramatically alongside utilization of other digital technologies. Despite promise and potential advantages for clinicians (including remote working, improved time management and safety) there are known drawbacks to telephone consultations for psychiatrists. This includes limitations to assessments of mental state and risk, with loss of non-verbal communication often cited as a point in favour of more sophisticated technologies such as video calling. By adopting telephone consultations to a greater extent during the initial months of the COVID-19 pandemic in the Coventry Crisis Resolution and Home Treatment Team (CRHTT), we aimed to assess the patient experience in telehealth, through a patient survey.

After an initial assessment or follow-up consultation with a medical practitioner from the crisis team, patients were invited to take part in a short questionnaire with a member of the administration staff. This consisted of eight questions on a Likert scale and three open questions for comments. Results were collated and analyzed via Microsoft Excel.

Most patients found the telephone consultations satisfactory, with more than 90% returning positive scores in understanding, convenience and overall satisfaction. All patients felt listened to and that their confidentiality was maintained; with all but one respondent willing to engage in further consultations via the telephone. Negative scores were typically returned for practical telephonic problems including poor signal, interference and background noise. In their comments patients expressed largely positive views about their experience with their clinician; analysis revealed key insights into the patient experience, demonstrating the convenience, comfort and flexibility possible with ‘telepsychiatry’.

Patient experience of telemedicine in a UK psychiatric crisis team is mostly positive, with clear advantages for both patients and clinicians. Our results show telephone consultations can be expanded to new patient assessments alongside follow-ups, enabling the team to reach a greater number of service users. This includes service users who are housebound due to infirmity, required to shield or have significant anxiety about the pandemic.

Two prominent risk factors for major depressive disorder (MDD) are childhood maltreatment (CM) and familial risk for MDD. Despite having these risk factors, there are individuals who maintain mental health, i.e. are resilient, whereas others develop MDD. It is unclear which brain morphological alterations are associated with this kind of resilience. Interaction analyses of risk and diagnosis status are needed that can account for complex adaptation processes, to identify neural correlates of resilience.

We analyzed brain structural data (3T magnetic resonance imaging) by means of voxel-based morphometry (CAT12 toolbox), using a 2 × 2 design, comparing four groups (N = 804) that differed in diagnosis (healthy v. MDD) and risk profiles (low-risk, i.e. absence of CM and familial risk v. high-risk, i.e. presence of both CM and familial risk). Using regions of interest (ROIs) from the literature, we conducted an interaction analysis of risk and diagnosis status.

Volume in the left middle frontal gyrus (MFG), part of the dorsolateral prefrontal cortex (DLPFC), was significantly higher in healthy high-risk individuals. There were no significant results for the bilateral superior frontal gyri, frontal poles, pars orbitalis of the inferior frontal gyri, and the right MFG.

The healthy high-risk group had significantly higher volumes in the left DLPFC compared to all other groups. The DLPFC is implicated in cognitive and emotional processes, and higher volume in this area might aid high-risk individuals in adaptive coping in order to maintain mental health. This increased volume might therefore constitute a neural correlate of resilience to MDD in high risk.