University of Münster, Institute for Translational Psychiatry, Münster, Germany.
University of Münster, Department of Mathematics and Computer Science, Münster, Germany.
JAMA Psychiatry. 2022 Sep 1;79(9):879-888. doi: 10.1001/jamapsychiatry.2022.1780.
Identifying neurobiological differences between patients with major depressive disorder (MDD) and healthy individuals has been a mainstay of clinical neuroscience for decades. However, recent meta-analyses have raised concerns regarding the replicability and clinical relevance of brain alterations in depression.
To quantify the upper bounds of univariate effect sizes, estimated predictive utility, and distributional dissimilarity of healthy individuals and those with depression across structural magnetic resonance imaging (MRI), diffusion-tensor imaging, and functional task-based as well as resting-state MRI, and to compare results with an MDD polygenic risk score (PRS) and environmental variables.
DESIGN, SETTING, AND PARTICIPANTS: This was a cross-sectional, case-control clinical neuroimaging study. Data were part of the Marburg-Münster Affective Disorders Cohort Study. Patients with depression and healthy controls were recruited from primary care and the general population in Münster and Marburg, Germany. Study recruitment was performed from September 11, 2014, to September 26, 2018. The sample comprised patients with acute and chronic MDD as well as healthy controls in the age range of 18 to 65 years. Data were analyzed from October 29, 2020, to April 7, 2022.
Primary analyses included univariate partial effect size (η2), classification accuracy, and distributional overlapping coefficient for healthy individuals and those with depression across neuroimaging modalities, controlling for age, sex, and additional modality-specific confounding variables. Secondary analyses included patient subgroups for acute or chronic depressive status.
A total of 1809 individuals (861 patients [47.6%] and 948 controls [52.4%]) were included in the analysis (mean [SD] age, 35.6 [13.2] years; 1165 female patients [64.4%]). The upper bound of the effect sizes of the single univariate measures displaying the largest group difference ranged from partial η2 of 0.004 to 0.017, and distributions overlapped between 87% and 95%, with classification accuracies ranging between 54% and 56% across neuroimaging modalities. This pattern remained virtually unchanged when considering either only patients with acute or chronic depression. Differences were comparable with those found for PRS but substantially smaller than for environmental variables.
Results of this case-control study suggest that even for maximum univariate biological differences, deviations between patients with MDD and healthy controls were remarkably small, single-participant prediction was not possible, and similarity between study groups dominated. Biological psychiatry should facilitate meaningful outcome measures or predictive approaches to increase the potential for a personalization of the clinical practice.
几十年来，识别重度抑郁症（MDD）患者和健康个体之间的神经生物学差异一直是临床神经科学的主要内容。然而，最近的荟萃分析对抑郁症患者大脑改变的可重复性和临床相关性提出了担忧。
量化健康个体和抑郁个体在结构磁共振成像（MRI）、弥散张量成像以及功能任务和静息态 MRI 上的单变量效应大小、估计预测效用和分布差异的上限，并将结果与 MDD 多基因风险评分（PRS）和环境变量进行比较。
设计、地点和参与者：这是一项横断面病例对照临床神经影像学研究。数据来自马尔堡-明斯特情感障碍队列研究。德国明斯特和马尔堡的初级保健和普通人群中招募了抑郁症患者和健康对照者。研究招募于 2014 年 9 月 11 日至 2018 年 9 月 26 日进行。该样本包括年龄在 18 至 65 岁之间的急性和慢性 MDD 患者以及健康对照者。数据分析于 2020 年 10 月 29 日至 2022 年 4 月 7 日进行。
主要分析包括控制年龄、性别和其他模态特定混杂变量后，健康个体和抑郁个体在神经影像学模态上的单变量偏效应大小（η2）、分类准确性和分布重叠系数。次要分析包括急性或慢性抑郁状态的患者亚组。
共纳入 1809 人（861 名患者[47.6%]和 948 名对照[52.4%]）（平均[标准差]年龄，35.6[13.2]岁；1165 名女性患者[64.4%]）。显示最大组间差异的单个单变量测量的效应大小上限范围为 0.004 至 0.017 的偏η2，分布重叠在 87%至 95%之间，跨神经影像学模态的分类准确性在 54%至 56%之间。当仅考虑急性或慢性抑郁症患者时，这种模式几乎没有变化。这些差异与 PRS 发现的差异相当，但与环境变量的差异要小得多。
这项病例对照研究的结果表明，即使对于最大的单变量生物学差异，MDD 患者和健康对照者之间的偏差也非常小，单个参与者的预测是不可能的，而且研究组之间的相似性占主导地位。生物精神病学应该促进有意义的结果测量或预测方法，以增加临床实践个性化的潜力。
