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Background: Depressive symptoms seem to be interrelated in a complex and self-reinforcing way. To gain a better understanding of this complexity, the inclusion of theoretically relevant constructs (such as risk and protective factors) offers a comprehensive view into the complex mechanisms underlying depression., Methods: Cross-sectional data from individuals diagnosed with a major depressive disorder (N = 986) and healthy controls (N = 1049) were analyzed. Participants self-reported their depressive symptoms, as well as several risk factors and protective factors. Regularized partial correlation networks were estimated for each group and compared using a network comparison test., Results: Symptoms of depression were more strongly connected in the network of depressed patients than in healthy controls. Among the risk factors, perceived stress, the experience of negative life events, emotional neglect, and emotional abuse were the most centrally embedded in both networks. However, the centrality of risk factors did not significantly differ between the two groups. Among the protective factors, social support, personal competence, and acceptance were the most central in both networks, where the latter was significantly more strongly associated with the symptom of self-hate in depressed patients., Conclusion: The network analysis revealed that key symptoms of depression were more strongly connected for depressed patients than for healthy controls, and that risk and protective factors play an important role, particularly perceived stress in both groups and an accepting attitude for depressed patients. However, the purpose of this study is hypothesis generating and assisting in the potential selection of non-symptom nodes for future research., Competing Interests: Declaration of competing interest We report no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: The second-generation antipsychotic (SGA) quetiapine is an essential option for antidepressant augmentation therapy in major depressive disorder (MDD), yet neurobiological mechanisms behind its antidepressant properties remain unclear. As SGAs interfere with activity in reward-related brain areas, including the anterior cingulate cortex (ACC) - a key brain region in antidepressant interventions, this study examined whether quetiapine treatment affects ACC activity during reward processing in MDD patients., Methods: Using the ACC as region of interest, an independent t-test comparing reward-related BOLD response of 51 quetiapine-taking and 51 antipsychotic-free MDD patients was conducted. Monetary reward outcome feedback was measured in a card-guessing paradigm using pseudorandom blocks. Participants were matched for age, sex, and depression severity and analyses were controlled for confounding variables, including total antidepressant medication load, illness chronicity and acute depression severity. Potential dosage effects were examined in a 3 × 1 ANOVA. Differences in ACC-related functional connectivity were assessed in psycho-physiological interaction (PPI) analyses., Results: Left subgenual ACC activity was significantly higher in the quetiapine group compared to antipsychotic-free participants and dependent on high-dose quetiapine intake. Results remained significant after controlling for confounding variables. The PPI analysis did not yield significant group differences in ACC-related functional connectivity., Limitations: Causal interpretation is limited due to cross-sectional findings., Conclusion: Elevated subgenual ACC activity to rewarding stimuli may represent a neurobiological marker and potential key interface of quetiapine's antidepressant effects in MDD. These results underline ACC activity during reward processing as an investigative avenue for future research and therapeutic interventions to improve MDD treatment outcomes., Competing Interests: Conflict of interest All authors declare that they have no conflict of interest., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Digital acquisition of patients' self-reports on individual risk factors and symptom severity represents a promising, cost-efficient, and increasingly prevalent approach for standardized data collection in psychiatric clinical routine. Yet, studies investigating digital data collection in patients with a schizophrenia spectrum disorder (PSSDs) are scarce. The objective of this study was to explore the feasibility of digitally acquired self-report assessments of risk and symptom profiles at the time of admission into inpatient treatment in an age-representative sample of hospitalized PSSDs. We investigated the required support, the data entry pace, and the subjective user experience. Findings were compared with those of patients with an affective disorder (PADs). Of 82 PSSDs who were eligible for inclusion, 59.8% (n=49) agreed to participate in the study, of whom 54.2% (n=26) could enter data without any assistance. Inclusion rates, drop-out rates, and subjective experience ratings did not differ between PSSDs and PADs. Patients reported high satisfaction with the assessment. PSSDs required more support and time for the data entry than PADs. Our results indicate that digital data collection is a feasible and well-received method in PSSDs. Future clinical and research efforts on digitized assessments in psychiatry should include PSSDs and offer support to reduce digital exclusion., Competing Interests: Conflict of Interest The authors have no conflicts of interest to declare that are relevant to the content of this article., (Copyright © 2022. Published by Elsevier B.V.)

Background: Among mental disorders, major depressive disorder (MDD) is highly prevalent and associated with emotional dysfunctions linked to activity alterations in the brain, mainly in prefrontal regions, the insula, the anterior cingulate cortex and the amygdala. However, this evidence is heterogeneous, perhaps because magnetic resonance imaging (MRI) studies on MDD tend to neglect comorbid anxiety (COM-A)., Methods: To address this, here a sample of age- and sex-matched patients, n MDD  = 90 and n COM-A  = 85, underwent functional MRI to assess neurofunctional group differences during a negative emotional face-matching task using a hypothesis-driven region of interest approach (dorsolateral prefrontal cortex, insula, anterior cingulate cortex, amygdala) and an explorative whole-brain approach. We also assessed these relationships with state-trait anxiety measures, a state depression measure, general functioning and medication load., Results: During face processing, COM-A (compared to MDD) had significantly increased bilateral insula activity. No activity differences were found in the anterior cingulate cortex or the amygdala. Whole-brain analyses revealed increased inferior temporal activation and frontal activation (comprising the inferior and middle frontal gyrus) in COM-A that was positively linked to state anxiety as well as general functioning across groups., Limitations: Still, the lack of a healthy control and small effects mean this study should be replicated to further interpret the results., Conclusions: The findings highlight a discriminative activation pattern between MDD and COM-A regarding emotion processing and may present a correlate of potentially anxiety-related psychopathology. In future, further investigations in potential discriminative activity patterns could help to elucidate the origin, development and treatment of depression., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: The diathesis-stress model of major depressive disorder (MDD) predicts interactions of recent stressful life events (SLEs) in adulthood and early developmental risk factors. We tested, for the first time, the diathesis stress model on brain structure in a large group of MDD patients., Methods: Structural magnetic resonance imaging data of 1465 participants (656 with lifetime diagnosis MDD; 809 healthy controls) were analyzed using voxel-based morphometry to identify clusters associated with recent SLEs (Life Events Questionnaire). Those clusters were then examined for group (healthy/MDD) × early developmental risk (operationalized as childhood abuse [Childhood Trauma Questionnaire] and a major psychiatric disorder [i.e., MDD, bipolar disorder, schizophrenia, and schizoaffective disorder] in a first-degree relative) × recent SLEs three-way interactions on grey matter volume., Results: There was a group × childhood abuse × recent SLEs interaction on left medial orbitofrontal cortex grey matter volume. This three-way interaction arose because childhood abuse and recent SLEs interacted in MDD subjects but not in healthy subjects., Limitations: We are not able to draw conclusions about the cause and effect relationship due to our cross-sectional study design., Conclusions: Our data provides evidence for an interplay between orbitofrontal cortex structure, childhood abuse and recent SLEs. These factors have previously been linked to MDD and their complex interaction contributes to the pathogenesis of MDD., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Smartphone-based monitoring constitutes a cost-effective instrument to assess and predict affective symptom trajectories. Large-scale transdiagnostic studies utilizing this methodology are yet lacking in psychiatric research. Thus, we introduce the Remote Monitoring Application in Psychiatry (ReMAP) and evaluate its feasibility and adherence in a large transdiagnostic sample., Methods: The ReMAP app was distributed among n = 997 healthy control participants and psychiatric patients, including affective, anxiety, and psychotic disorders. Passive sensor data (acceleration, geolocation, walking distance, steps), optional standardized self-reports on mood and sleep, and voice samples were assessed. Feasibility and adherence were evaluated based on frequency of transferred data, and participation duration. Preliminary results are presented while data collection is ongoing., Results: Retention rates of 90.25% for the minimum study duration of two weeks and 33.09% for one year were achieved (median participation 135 days, IQR=111). Participants transferred an average of 51.83 passive events per day. An average of 34.59 self-report events were transferred per user, with a considerable range across participants (0-552 events). Clinical and non-clinical subgroups did not differ in participation duration or rate of data transfer. The mean rate of days with passive data was higher and less heterogeneous in iOS (91.85%, SD=21.25) as compared to Android users (63.04%, SD=35.09)., Limitations: Subjective user experience was not assessed limiting conclusions about app acceptance., Conclusions: ReMAP is a technically feasible tool to assess affective symptoms with high temporal resolution in large-scale transdiagnostic samples with good adherence. Future studies should account for differences between operating systems., (Copyright © 2021. Published by Elsevier B.V.)