School of Information Science and Engineering, Southeast University, Nanjing, 210096, China.
Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, 210009, China.
J Affect Disord. 2018 Aug 1;235:544-550. doi: 10.1016/j.jad.2018.04.065. Epub 2018 Apr 10.
Abnormal functional connectivity (FC) in the default mode network (DMN) plays an important role in late-onset depression (LOD) patients. In this study, the risk predictors of LOD based on anterior and posterior DMN are explored.
A total of 27 LOD patients and 40 healthy controls (HC) underwent resting-state functional magnetic resonance imaging and cognitive assessments. Firstly, FCs within DMN sub-networks were determined by placing seeds in the ventral medial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC). Secondly, multivariable logistic regression was used to identify risk factors for LOD patients. Finally, correlation analysis was performed to investigate the relationship between risk factors and the cognitive value.
Multivariable logistic regression showed that the FCs between the vmPFC and right middle temporal gyrus (MTG) (vmPFC-MTG_R), FCs between the vmPFC and left precuneus (PCu), and FCs between the PCC and left PCu (PCC-PCu_L) were the risk factors for LOD. Furthermore, FCs of the vmPFC-MTG_R and PCC-PCu_L correlated with processing speed (R = 0.35, P = 0.002; R = 0.32, P = 0.009), and FCs of the vmPFC-MTG_R correlated with semantic memory (R = 0.41, P = 0.001).
The study was a cross-sectional study. The results may be potentially biased because of a small sample.
In this study, we confirmed that LOD patients mainly present cognitive deficits in processing speed and semantic memory. Moreover, our findings further suggested that FCs within DMN sub-networks associated with cognitions were risk factors, which may be used for the prediction of LOD.
默认模式网络（DMN）中的异常功能连接（FC）在迟发性抑郁症（LOD）患者中起着重要作用。本研究旨在探讨基于前、后 DMN 的 LOD 风险预测因子。
共纳入 27 例 LOD 患者和 40 例健康对照者（HC）进行静息态功能磁共振成像和认知评估。首先，在腹内侧前额叶皮质（vmPFC）和后扣带回皮质（PCC）中放置种子以确定 DMN 子网络内的 FC。其次，采用多变量逻辑回归识别 LOD 患者的风险因素。最后，进行相关性分析以探讨风险因素与认知值之间的关系。
多变量逻辑回归显示，vmPFC 与右侧颞中回（MTG）之间的 FC（vmPFC-MTG_R）、vmPFC 与左侧楔前叶（PCu）之间的 FC 以及 PCC 与左侧 PCu 之间的 FC（PCC-PCu_L）是 LOD 的风险因素。此外，vmPFC-MTG_R 和 PCC-PCu_L 的 FC 与处理速度相关（R=0.35，P=0.002；R=0.32，P=0.009），vmPFC-MTG_R 的 FC 与语义记忆相关（R=0.41，P=0.001）。
本研究为横断面研究，可能会因样本量小而导致结果存在潜在偏倚。
本研究证实，LOD 患者主要表现为处理速度和语义记忆方面的认知缺陷。此外，我们的研究结果进一步表明，与认知相关的 DMN 子网络内的 FC 是风险因素，可用于 LOD 的预测。
