Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.

In 410 male and female participants aged 17–35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPIbipolar scale; n = 208), patients with a DSM-IV-TR diagnosis of BD (n = 87), and healthy controls (n = 115) using voxel-based morphometry in SPM12/CAT12. We applied conjunction analyses to identify similarities in gray matter volume alterations in individuals at risk and BD patients, relative to healthy controls. We also performed exploratory whole-brain analyses to identify differences in gray matter volume among groups. ComBat was used to harmonize imaging data from seven sites.

Both individuals at risk and BD patients showed larger volumes in the right putamen than healthy controls. Furthermore, individuals at risk had smaller volumes in the right inferior occipital gyrus, and BD patients had larger volumes in the left precuneus, compared to healthy controls. These findings were independent of course of illness (number of lifetime manic and depressive episodes, number of hospitalizations), comorbid diagnoses (major depressive disorder, attention-deficit hyperactivity disorder, anxiety disorder, eating disorder), familial risk, current disease severity (global functioning, remission status), and current medication intake.

Our findings indicate that alterations in the right putamen might constitute a vulnerability marker for BD.

Depression and anxiety are the leading contributors to the global burden of disease among young people, accounting for over a third (34.8%) of years lived with disability. Yet there is limited evidence for interventions that prevent adolescent depression and anxiety in low- and middle-income countries (LMICs), where 90% of adolescents live. This article introduces the ‘Improving Adolescent mentaL health by reducing the Impact of poVErty (ALIVE)’ study, its conceptual framework, objectives, methods and expected outcomes. The aim of the ALIVE study is to develop and pilot-test an intervention that combines poverty reduction with strengthening self-regulation to prevent depression and anxiety among adolescents living in urban poverty in Colombia, Nepal and South Africa.

This aim will be achieved by addressing four objectives: (1) develop a conceptual framework that identifies the causal mechanisms linking poverty, self-regulation and depression and anxiety; (2) develop a multi-component selective prevention intervention targeting self-regulation and poverty among adolescents at high risk of developing depression or anxiety; (3) adapt and validate instruments to measure incidence of depression and anxiety, mediators and implementation parameters of the prevention intervention; and (4) undertake a four-arm pilot cluster randomised controlled trial to assess the feasibility, acceptability and cost of the selective prevention intervention in the three study sites.

The contributions of this study include the active engagement and participation of adolescents in the research process; a focus on the causal mechanisms of the intervention; building an evidence base for prevention interventions in LMICs; and the use of an interdisciplinary approach.

By developing and evaluating an intervention that addresses multidimensional poverty and self-regulation, ALIVE can make contributions to evidence on the integration of mental health into broader development policy and practice.

Individuals with bipolar disorder are commonly correctly diagnosed a decade after symptom onset. Machine learning techniques may aid in early recognition and reduce the disease burden. As both individuals at risk and those with a manifest disease display structural brain markers, structural magnetic resonance imaging may provide relevant classification features.

Following a pre-registered protocol, we trained linear support vector machine (SVM) to classify individuals according to their estimated risk for bipolar disorder using regional cortical thickness of help-seeking individuals from seven study sites (N = 276). We estimated the risk using three state-of-the-art assessment instruments (BPSS-P, BARS, EPIbipolar).

For BPSS-P, SVM achieved a fair performance of Cohen's κ of 0.235 (95% CI 0.11–0.361) and a balanced accuracy of 63.1% (95% CI 55.9–70.3) in the 10-fold cross-validation. In the leave-one-site-out cross-validation, the model performed with a Cohen's κ of 0.128 (95% CI −0.069 to 0.325) and a balanced accuracy of 56.2% (95% CI 44.6–67.8). BARS and EPIbipolar could not be predicted. In post hoc analyses, regional surface area, subcortical volumes as well as hyperparameter optimization did not improve the performance.

Individuals at risk for bipolar disorder, as assessed by BPSS-P, display brain structural alterations that can be detected using machine learning. The achieved performance is comparable to previous studies which attempted to classify patients with manifest disease and healthy controls. Unlike previous studies of bipolar risk, our multicenter design permitted a leave-one-site-out cross-validation. Whole-brain cortical thickness seems to be superior to other structural brain features.

COVID-19 altered research in Clinical and Translational Science Award (CTSA) hubs in an unprecedented manner, leading to adjustments for COVID-19 research.

CTSA members volunteered to conduct a review on the impact of CTSA network on COVID-19 pandemic with the assistance from NIH survey team in October 2020. The survey questions included the involvement of CTSAs in decision-making concerning the prioritization of COVID-19 studies. Descriptive and statistical analyses were conducted to analyze the survey data.

60 of the 64 CTSAs completed the survey. Most CTSAs lacked preparedness but promptly responded to the pandemic. Early disruption of research triggered, enhanced CTSA engagement, creation of dedicated research areas and triage for prioritization of COVID-19 studies. CTSAs involvement in decision-making were 16.75 times more likely to create dedicated diagnostic laboratories (95% confidence interval [CI] = 2.17–129.39; P < 0.01). Likewise, institutions with internal funding were 3.88 times more likely to establish COVID-19 dedicated research (95% CI = 1.12–13.40; P < 0.05). CTSAs were instrumental in securing funds and facilitating establishment of laboratory/clinical spaces for COVID-19 research. Workflow was modified to support contracting and IRB review at most institutions with CTSAs. To mitigate chaos generated by competing clinical trials, central feasibility committees were often formed for orderly review/prioritization.

The lessons learned from the COVID-19 pandemic emphasize the pivotal role of CTSAs in prioritizing studies and establishing the necessary research infrastructure, and the importance of prompt and flexible research leadership with decision-making capacity to manage future pandemics.

It has been shown that patients with schizophrenia are super-sensitive towards dopamine-releasing agents such as amphetamine. Here, we studied the effects of amphetamine sensitization on amphetamine-induced dopamine release in healthy subjects.

To measure d-amphetamine-induced dopamine release as measured with the D2,3 agonist radioligand [11C]-(+)-PHNO-PET via change in non-displacable binding potential (BPND) and behavioral measures of d-amphetamine effects with drug effects questionnaire (DEQ) and subjective states questionnaire (SSQ).

To study d-amphetamine-induced sensitization in healthy subjects on a behavioral and neurochemical level with [11C]-(+)-PHNO-PET in order to gain more knowledge on sensitization-induced changes in the dopaminergic system.

Twelve stimulant-naïve healthy male subjects underwent three 90-min [11C]-(+)-PHNO-PET-scans and four oral administrations of d-amphetamine. After a naïve baseline scan, subjects underwent a PET scan with previous ingestion of 0.4 mg/kg bodyweight of d-amphetamine 90–120 minutes before scanning. Subsequently, subjects were sensitized to d-amphetamine with the same dose on two separate days. Thereafter, they underwent another PET scan with previous d-amphetamine ingestion. DEQ and SSQ were administered before, 60 min, 90–120 min, and 210 min after amphetamine ingestion.

We found significant sensitization effects on a behavioral level and on a neurochemical level after four administrations of amphetamine. Items of the SSQ, which showed significant sensitization effects were “outgoing”, “energetic”, “lively”, “alert” and “focused”.

We were able to induce significant behavioral and neurochemical sensitization in healthy humans, which were measured with [11C]-(+)-PHNO-PET for the first time. This sensitization model will be useful for studying the neurobiology of schizophrenia.

The authors have not supplied their declaration of competing interest.