Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China.
Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Transl Psychiatry. 2024 Aug 31;14(1):351. doi: 10.1038/s41398-024-03062-z.
Previous research has established associations between amygdala functional connectivity abnormalities and major depressive disorder (MDD). However, inconsistencies persist due to limited sample sizes and poorly elucidated transcriptional patterns. In this study, we aimed to address these gaps by analyzing a multicenter magnetic resonance imaging (MRI) dataset consisting of 210 first-episode, drug-naïve MDD patients and 363 age- and sex-matched healthy controls (HC). Using Pearson correlation analysis, we established individualized amygdala functional connectivity patterns based on the Automated Anatomical Labeling (AAL) atlas. Subsequently, machine learning techniques were employed to evaluate the diagnostic utility of amygdala functional connectivity for identifying MDD at the individual level. Additionally, we investigated the spatial correlation between MDD-related amygdala functional connectivity alterations and gene expression through Pearson correlation analysis. Our findings revealed reduced functional connectivity between the amygdala and specific brain regions, such as frontal, orbital, and temporal regions, in MDD patients compared to HC. Importantly, amygdala functional connectivity exhibited robust discriminatory capability for characterizing MDD at the individual level. Furthermore, we observed spatial correlations between MDD-related amygdala functional connectivity alterations and genes enriched for metal ion transport and modulation of chemical synaptic transmission. These results underscore the significance of amygdala functional connectivity alterations in MDD and suggest potential neurobiological mechanisms and markers for these alterations.
先前的研究已经确立了杏仁核功能连接异常与重度抑郁症（MDD）之间的关联。然而，由于样本量有限和转录模式未阐明，这些研究结果并不一致。在这项研究中，我们旨在通过分析由 210 名首发、未用药的 MDD 患者和 363 名年龄和性别匹配的健康对照（HC）组成的多中心磁共振成像（MRI）数据集来解决这些差距。我们使用 Pearson 相关分析，基于自动解剖标记（AAL）图谱，建立了个体化的杏仁核功能连接模式。随后，我们使用机器学习技术评估了杏仁核功能连接在个体水平上识别 MDD 的诊断效用。此外，我们通过 Pearson 相关分析研究了与 MDD 相关的杏仁核功能连接改变与基因表达之间的空间相关性。我们的研究结果表明，与 HC 相比，MDD 患者的杏仁核与额、眶和颞等特定脑区之间的功能连接减少。重要的是，杏仁核功能连接在个体水平上对 MDD 具有强大的区分能力。此外，我们观察到与 MDD 相关的杏仁核功能连接改变与富集的金属离子转运和化学突触传递调节基因之间存在空间相关性。这些结果强调了杏仁核功能连接改变在 MDD 中的重要性，并提示了这些改变的潜在神经生物学机制和标志物。
