TY - JOUR A1 - Förstner, Bernd Rainer A1 - Böttger, Sarah Jane A1 - Moldavski, Alexander A1 - Bajbouj, Malek A1 - Pfennig, Andrea A1 - Manook, Andre A1 - Ising, Marcus A1 - Pittig, Andre A1 - Heinig, Ingmar A1 - Heinz, Andreas A1 - Mathiak, Klaus A1 - Schulze, Thomas G. A1 - Schneider, Frank A1 - Kamp-Becker, Inge A1 - Meyer-Lindenberg, Andreas A1 - Padberg, Frank A1 - Banaschewski, Tobias A1 - Bauer, Michael A1 - Rupprecht, Rainer A1 - Wittchen, Hans-Ulrich A1 - Rapp, Michael A. A1 - Tschorn, Mira T1 - The associations of positive and negative valence systems, cognitive systems and social processes on disease severity in anxiety and depressive disorders JF - Frontiers in psychiatry N2 - Background Anxiety and depressive disorders share common features of mood dysfunctions. This has stimulated interest in transdiagnostic dimensional research as proposed by the Research Domain Criteria (RDoC) approach by the National Institute of Mental Health (NIMH) aiming to improve the understanding of underlying disease mechanisms. The purpose of this study was to investigate the processing of RDoC domains in relation to disease severity in order to identify latent disorder-specific as well as transdiagnostic indicators of disease severity in patients with anxiety and depressive disorders. Methods Within the German research network for mental disorders, 895 participants (n = 476 female, n = 602 anxiety disorder, n = 257 depressive disorder) were recruited for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) and included in this cross-sectional study. We performed incremental regression models to investigate the association of four RDoC domains on disease severity in patients with affective disorders: Positive (PVS) and Negative Valance System (NVS), Cognitive Systems (CS) and Social Processes (SP). Results The results confirmed a transdiagnostic relationship for all four domains, as we found significant main effects on disease severity within domain-specific models (PVS: & beta; = -0.35; NVS: & beta; = 0.39; CS: & beta; = -0.12; SP: & beta; = -0.32). We also found three significant interaction effects with main diagnosis showing a disease-specific association. Limitations The cross-sectional study design prevents causal conclusions. Further limitations include possible outliers and heteroskedasticity in all regression models which we appropriately controlled for. Conclusion Our key results show that symptom burden in anxiety and depressive disorders is associated with latent RDoC indicators in transdiagnostic and disease-specific ways. KW - Research Domain Criteria KW - depression KW - anxiety disoders KW - disease severity KW - transdiagnostic KW - RDoC Y1 - 2023 U6 - https://doi.org/10.3389/fpsyt.2023.1161097 SN - 1664-0640 VL - 14 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Förstner, Bernd R. A1 - Tschorn, Mira A1 - Reinoso-Schiller, Nicolas A1 - Maričić, Lea Mascarell A1 - Röcher, Erik A1 - Kalman, Janos L. A1 - Stroth, Sanna A1 - Mayer, Annalina V. A1 - Schwarz, Kristina A1 - Kaiser, Anna A1 - Pfennig, Andrea A1 - Manook, André A1 - Ising, Marcus A1 - Heinig, Ingmar A1 - Pittig, Andre A1 - Heinz, Andreas A1 - Mathiak, Klaus A1 - Schulze, Thomas G. A1 - Schneider, Frank A1 - Kamp-Becker, Inge A1 - Meyer-Lindenberg, Andreas A1 - Padberg, Frank A1 - Banaschewski, Tobias A1 - Bauer, Michael A1 - Rupprecht, Rainer A1 - Wittchen, Hans-Ulrich A1 - Rapp, Michael A. T1 - Mapping research domain criteria using a transdiagnostic mini-RDoC assessment in mental disorders: a confirmatory factor analysis JF - European archives of psychiatry and clinical neuroscience N2 - This study aimed to build on the relationship of well-established self-report and behavioral assessments to the latent constructs positive (PVS) and negative valence systems (NVS), cognitive systems (CS), and social processes (SP) of the Research Domain Criteria (RDoC) framework in a large transnosological population which cuts across DSM/ICD-10 disorder criteria categories. One thousand four hundred and thirty one participants (42.1% suffering from anxiety/fear-related, 18.2% from depressive, 7.9% from schizophrenia spectrum, 7.5% from bipolar, 3.4% from autism spectrum, 2.2% from other disorders, 18.4% healthy controls, and 0.2% with no diagnosis specified) recruited in studies within the German research network for mental disorders for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) were examined with a Mini-RDoC-Assessment including behavioral and self-report measures. The respective data was analyzed with confirmatory factor analysis (CFA) to delineate the underlying latent RDoC-structure. A revised four-factor model reflecting the core domains positive and negative valence systems as well as cognitive systems and social processes showed a good fit across this sample and showed significantly better fit compared to a one factor solution. The connections between the domains PVS, NVS and SP could be substantiated, indicating a universal latent structure spanning across known nosological entities. This study is the first to give an impression on the latent structure and intercorrelations between four core Research Domain Criteria in a transnosological sample. We emphasize the possibility of using already existing and well validated self-report and behavioral measurements to capture aspects of the latent structure informed by the RDoC matrix. KW - Diagnosis and classification KW - Research Domain Criteria KW - PD-CAN KW - Confirmatory factor analysis CFA KW - RDoC KW - Transdiagnostic Y1 - 2022 U6 - https://doi.org/10.1007/s00406-022-01440-6 SN - 0940-1334 SN - 1433-8491 VL - 273 IS - 3 SP - 527 EP - 539 PB - Springer Nature CY - Heidelberg ER -