There has been a marked increase of network studies of Major Depressive Disorder (MDD). Despite rapidly growing contributions, their findings have yet to be systematically aggregated and examined. We therefore conducted a systematic review of depression network studies using PRISMA guidelines. A total of 254 clinical and population studies were collected from ISI's Web of Science and PsycINFO, between January 2010 to May 2020. A total of 23 between-subject studies were included for review, resulting in 58 cross-sectional networks. To determine their most critical symptoms and their connections, we analyzed strength centrality rankings, and aggregated the most robust symptoms connections into a summary network. Results indicated substantial variability between study samples, depression measures, and network features. Fatigue and Depressed Mood were the most central symptoms, while Weight changes tended to have the weakest centrality. Depressed Mood and Fatigue formed two separated symptoms communities characterized by recurrent connections, with Mood-Anhedonia as the most frequent edge of MDD. Network analysis informed our understanding of MDD, suggesting the critical role of Fatigue and Depressed Mood. The study's findings are discussed in their clinical and methodological implications, including future directions for network studies of MDD.

重度抑郁症 (MDD) 的网络研究显着增加。尽管贡献迅速增加，但他们的发现尚未系统地汇总和检查。因此，我们使用 PRISMA 指南对抑郁症网络研究进行了系统回顾。2010 年 1 月至 2020 年 5 月期间，从 ISI 的科学网络和 PsycINFO 收集了总共 254 项临床和人群研究。总共纳入了 23 项受试者间研究进行审查，产生了 58 个横断面网络。为了确定他们最关键的症状及其联系，我们分析了强度中心性排名，并将最稳健的症状联系汇总到一个汇总网络中。结果表明研究样本、抑郁量度和网络特征之间存在很大差异。疲劳和情绪低落是最主要的症状，而体重变化的中心性往往最弱。抑郁情绪和疲劳形成了两个以反复连接为特征的独立症状社区，情绪-快感缺失是 MDD 最常见的边缘。网络分析告诉我们对 MDD 的理解，表明疲劳和抑郁情绪的关键作用。该研究的结果在其临床和方法学意义中进行了讨论，包括 MDD 网络研究的未来方向。表明疲劳和抑郁情绪的关键作用。该研究的结果在其临床和方法学意义中进行了讨论，包括 MDD 网络研究的未来方向。表明疲劳和抑郁情绪的关键作用。该研究的发现在其临床和方法学意义中进行了讨论，包括 MDD 网络研究的未来方向。