Förstner Bernd R, Böttger Sarah Jane, Moldavski Alexander, Bajbouj Malek, Pfennig Andrea, Manook André, Ising Marcus, Pittig Andre, Heinig Ingmar, Heinz Andreas, Mathiak Klaus, Schulze Thomas G, Schneider Frank, Kamp-Becker Inge, Meyer-Lindenberg Andreas, Padberg Frank, Banaschewski Tobias, Bauer Michael, Rupprecht Rainer, Wittchen Hans-Ulrich, Rapp Michael A, Tschorn Mira
Social and Preventive Medicine, Department of Sports and Health Sciences, University of Potsdam, Potsdam, Germany.
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany.
Front Psychiatry. 2023 Jun 16;14:1161097. doi: 10.3389/fpsyt.2023.1161097. eCollection 2023.
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.
Within the German research network for mental disorders, 895 participants ( = 476 female, = 602 anxiety disorder, = 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).
The results confirmed a transdiagnostic relationship for all four domains, as we found significant main effects on disease severity within domain-specific models (PVS: = -0.35; NVS: = 0.39; CS: = -0.12; SP: = -0.32). We also found three significant interaction effects with main diagnosis showing a disease-specific association.
The cross-sectional study design prevents causal conclusions. Further limitations include possible outliers and heteroskedasticity in all regression models which we appropriately controlled for.
Our key results show that symptom burden in anxiety and depressive disorders is associated with latent RDoC indicators in transdiagnostic and disease-specific ways.
焦虑症和抑郁症具有情绪功能障碍的共同特征。这激发了人们对跨诊断维度研究的兴趣，正如美国国立精神卫生研究所（NIMH）的研究领域标准（RDoC）方法所提议的，旨在增进对潜在疾病机制的理解。本研究的目的是调查RDoC领域与疾病严重程度的关系，以确定焦虑症和抑郁症患者疾病严重程度的潜在疾病特异性以及跨诊断指标。
在德国精神障碍研究网络中，招募了895名参与者（n = 476名女性，n = 602名焦虑症患者，n = 257名抑郁症患者）参与德国表型、诊断和临床领域评估网络（PD-CAN），并纳入本横断面研究。我们进行了逐步回归模型，以研究情感障碍患者中四个RDoC领域与疾病严重程度的关联：正性（PVS）和负性效价系统（NVS）、认知系统（CS）和社会过程（SP）。
结果证实了所有四个领域的跨诊断关系，因为我们在特定领域模型中发现了对疾病严重程度的显著主效应（PVS：β = -0.35；NVS：β = 0.39；CS：β = -0.12；SP：β = -0.32）。我们还发现了三个与主要诊断的显著交互效应，显示出疾病特异性关联。
横断面研究设计无法得出因果结论。进一步的局限性包括所有回归模型中可能存在的异常值和异方差性，我们对此进行了适当控制。
我们的主要结果表明，焦虑症和抑郁症的症状负担以跨诊断和疾病特异性的方式与潜在的RDoC指标相关。
