Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.
Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan.
BMC Psychiatry. 2023 Jan 24;23(1):63. doi: 10.1186/s12888-023-04560-y.
Although many studies have reported the biological basis of major depressive disorder (MDD), none have been put into practical use. Recently, we developed a generalizable brain network marker for MDD diagnoses (diagnostic marker) across multiple imaging sites using resting-state functional magnetic resonance imaging (rs-fMRI). We have planned this clinical trial to establish evidence for the practical applicability of this diagnostic marker as a medical device. In addition, we have developed generalizable brain network markers for MDD stratification (stratification markers), and the verification of these brain network markers is a secondary endpoint of this study.
This is a non-randomized, open-label study involving patients with MDD and healthy controls (HCs). We will prospectively acquire rs-fMRI data from 50 patients with MDD and 50 HCs and anterogradely verify whether our diagnostic marker can distinguish between patients with MDD and HCs. Furthermore, we will longitudinally obtain rs-fMRI and clinical data at baseline and 6 weeks later in 80 patients with MDD treated with escitalopram and verify whether it is possible to prospectively distinguish MDD subtypes that are expected to be effectively responsive to escitalopram using our stratification markers.
In this study, we will confirm that sufficient accuracy of the diagnostic marker could be reproduced for data from a prospective clinical study. Using longitudinally obtained data, we will also examine whether the "brain network marker for MDD diagnosis" reflects treatment effects in patients with MDD and whether treatment effects can be predicted by "brain network markers for MDD stratification". Data collected in this study will be extremely important for the clinical application of the brain network markers for MDD diagnosis and stratification.
Japan Registry of Clinical Trials ( jRCTs062220063 ). Registered 12/10/2022.
尽管许多研究已经报道了重度抑郁症（MDD）的生物学基础，但没有一项研究得到实际应用。最近，我们使用静息态功能磁共振成像（rs-fMRI）开发了一种可推广的用于 MDD 诊断的大脑网络标志物（诊断标志物），该标志物可在多个成像部位使用。我们已经计划了这项临床试验，以建立该诊断标志物作为医疗器械的实际适用性的证据。此外，我们还开发了用于 MDD 分层的可推广的大脑网络标志物（分层标志物），对这些大脑网络标志物的验证是本研究的次要终点。
这是一项非随机、开放标签的研究，涉及 MDD 患者和健康对照者（HCs）。我们将前瞻性地从 50 名 MDD 患者和 50 名 HCs 中采集 rs-fMRI 数据，并正向验证我们的诊断标志物是否可以区分 MDD 患者和 HCs。此外，我们将在 80 名接受依地普仑治疗的 MDD 患者中进行纵向研究，在基线和 6 周后获取 rs-fMRI 和临床数据，并验证是否可以使用我们的分层标志物前瞻性地区分预计对依地普仑有效反应的 MDD 亚型。
在这项研究中，我们将确认诊断标志物的足够准确性可以在前瞻性临床研究中重现。使用纵向获得的数据，我们还将检查“MDD 诊断的大脑网络标志物”是否反映了 MDD 患者的治疗效果，以及“MDD 分层的大脑网络标志物”是否可以预测治疗效果。本研究中收集的数据对于 MDD 诊断和分层的大脑网络标志物的临床应用将非常重要。
日本临床试验注册（jRCTs062220063）。注册于 2022 年 12 月 10 日。
