Healthcare workers (HCW) face tremendous challenges during the COVID-19 pandemic. Little is known about the subjective burden, views, and COVID-19 infection status of HCWs. The aim of this work was to evaluate the subjective burden, the perception of the information policies, and the agreement on structural measures in a large cohort of German HCW during the COVID-19 pandemic. This country-wide anonymous online survey was carried out from April 15th until May 1st, 2020. 25 content-related questions regarding the subjective burden and other dimensions were evaluated. We evaluated different dimensions of subjective burden, stress, and perspectives using 5-point Likert-scale questions. Moreover, the individual COVID-19 infection status, the amount of people infected in circle of friends and acquaintances and the hours working overtime were assessed. A total of 3669 HCWs provided sufficient responses for analyses. 2.8% of HCWs reported to have been tested positive for COVID-19. Nurses reported in principle higher ratings on all questions of subjective burden and stress than doctors and other hospital staff. Doctors (3.6%) and nurses (3.1%) were more likely to be tested positive for COVID-19 than other hospital staff (0.6%, Chi 2 (2) = 17.39, p < 0.0005). HCWs who worked in a COVID-19 environment reported higher levels of subjective burden and stress compared to all other participants. Working in a COVID-19 environment increased the likelihood to be tested positive for COVID-19 (4.8% vs. 2.3%, Chi 2 (1) = 12.62, p < 0.0005) and the severity of the subjective burden. During the COVID-19 pandemic, nurses experience more stress than doctors. Overall, German HCWs showed high scores of agreement with the measures taken by the hospitals.

Psychiatric disorders are ubiquitously characterized by debilitating social impairments. These difficulties are thought to emerge from aberrant social inference. In order to elucidate the underlying computational mechanisms, patients diagnosed with major depressive disorder (N = 29), schizophrenia (N = 31), and borderline personality disorder (N = 31) as well as healthy controls (N = 34) performed a probabilistic reward learning task in which participants could learn from social and non-social information. Patients with schizophrenia and borderline personality disorder performed more poorly on the task than healthy controls and patients with major depressive disorder. Broken down by domain, borderline personality disorder patients performed better in the social compared to the non-social domain. In contrast, controls and major depressive disorder patients showed the opposite pattern and schizophrenia patients showed no difference between domains. In effect, borderline personality disorder patients gave up a possible overall performance advantage by concentrating their learning in the social at the expense of the non-social domain. We used computational modeling to assess learning and decision-making parameters estimated for each participant from their behavior. This enabled additional insights into the underlying learning and decision-making mechanisms. Patients with borderline personality disorder showed slower learning from social and non-social information and an exaggerated sensitivity to changes in environmental volatility, both in the non-social and the social domain, but more so in the latter. Regarding decision-making the modeling revealed that compared to controls and major depression patients, patients with borderline personality disorder and schizophrenia showed a stronger reliance on social relative to non-social information when making choices. Depressed patients did not differ significantly from controls in this respect. Overall, our results are consistent with the notion of a general interpersonal hypersensitivity in borderline personality disorder and schizophrenia based on a shared computational mechanism characterized by an over-reliance on beliefs about others in making decisions and by an exaggerated need to make sense of others during learning specifically in borderline personality disorder.

Currently, the clinical diagnosis of schizophrenia relies solely on self-reporting and clinical interview, and likely comprises heterogeneous biological subsets. Such subsets may be defined by an underlying biology leading to solid biomarkers. A transgenic rat model modestly overexpressing the full-length, non-mutant Disrupted-in-Schizophrenia 1 (DISC1) protein (tgDISC1 rat) was generated that defines such a subset, inspired by our previous identification of insoluble DISC1 protein in post mortem brains from patients with chronic mental illness. Besides specific phenotypes such as DISC1 protein pathology, abnormal dopamine homeostasis, and changes in neuroanatomy and behavior, this animal model also shows subtle disturbances in overarching signaling pathways relevant for schizophrenia. In a reverse-translational approach, assuming that both the animal model and a patient subset share common disturbed signaling pathways, we identified differentially expressed transcripts from peripheral blood mononuclear cells of tgDISC1 rats that revealed an interconnected set of dysregulated genes, led by decreased expression of regulator of G-protein signaling 1 (RGS1), chemokine (C–C) ligand 4 (CCL4), and other immune-related transcripts enriched in T-cell and macrophage signaling and converging in one module after weighted gene correlation network analysis. Testing expression of this gene network in two independent cohorts of patients with schizophrenia versus healthy controls ( n = 16/50 and n = 54/45) demonstrated similar expression changes. The two top markers RGS1 and CCL4 defined a subset of 27% of patients with 97% specificity. Thus, analogous aberrant signaling pathways can be identified by a blood test in an animal model and a corresponding schizophrenia patient subset, suggesting that in this animal model tailored pharmacotherapies for this patient subset could be achieved.

Even today, patients with schizophrenia often have an unfavorable outcome. Negative symptoms and cognitive deficits are common features in many patients and prevent recovery. In recent years, aerobic endurance training has emerged as a therapeutic approach with positive effects on several domains of patients’ health. However, appropriately sized, multicenter randomized controlled trials that would allow better generalization of results are lacking. The exercise study presented here is a multicenter, rater-blind, two-armed, parallel-group randomized clinical trial in patients with clinically stable schizophrenia being conducted at five German tertiary hospitals. The intervention group performs aerobic endurance training on bicycle ergometers three times per week for 40–50 min/session (depending on the intervention week) for a total of 26 weeks, and the control group performs balance and tone training for the same amount of time. Participants are subsequently followed up for 26 weeks. The primary endpoint is all-cause discontinuation; secondary endpoints include psychopathology, cognition, daily functioning, cardiovascular risk factors, and explorative biological measures regarding the underlying mechanisms of exercise. A total of 180 patients will be randomized. With currently 162 randomized participants, our study is the largest trial to date to investigate endurance training in patients with schizophrenia. We hypothesize that aerobic endurance training has beneficial effects on patients’ mental and physical health, leading to lower treatment discontinuation rates and improving disease outcomes. The study results will provide a basis for recommending exercise interventions as an add-on therapy in patients with schizophrenia.The study is registered in the International Clinical Trials Database (ClinicalTrials.gov identifier [NCT number]: NCT03466112) and in the German Clinical Trials Register (DRKS-ID: DRKS00009804).

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