Department of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China.
Aging (Albany NY). 2024 Jun 13;16(12):10299-10320. doi: 10.18632/aging.205930.
This study aimed to identify key clock genes closely associated with major depressive disorder (MDD) using bioinformatics and machine learning approaches.
Gene expression data of 128 MDD patients and 64 healthy controls from blood samples were obtained. Differentially expressed were identified and weighted gene co-expression network analysis (WGCNA) was first performed to screen MDD-related key genes. These genes were then intersected with 1475 known circadian rhythm genes to identify circadian rhythm genes associated with MDD. Finally, multiple machine learning algorithms were applied for further selection, to determine the most critical 4 circadian rhythm biomarkers.
Four key circadian rhythm genes (ABCC2, APP, HK2 and RORA) were identified that could effectively distinguish MDD samples from controls. These genes were significantly enriched in circadian pathways and showed strong correlations with immune cell infiltration. Drug target prediction suggested that small molecules like melatonin and escitalopram may target these circadian rhythm proteins.
This study revealed discovered 4 key circadian rhythm genes closely associated with MDD, which may serve as diagnostic biomarkers and therapeutic targets. The findings highlight the important roles of circadian disruptions in the pathogenesis of MDD, providing new insights for precision diagnosis and targeted treatment of MDD.
本研究旨在通过生物信息学和机器学习方法，鉴定与重度抑郁症（MDD）密切相关的关键时钟基因。
从血液样本中获得了 128 名 MDD 患者和 64 名健康对照者的基因表达数据。首先进行差异表达鉴定，然后进行加权基因共表达网络分析（WGCNA）筛选与 MDD 相关的关键基因。将这些基因与 1475 个已知的生物钟基因进行交叉，以鉴定与 MDD 相关的生物钟基因。最后，应用多种机器学习算法进行进一步选择，以确定最关键的 4 个生物钟生物标志物。
鉴定出 4 个关键的生物钟基因（ABCC2、APP、HK2 和 RORA），可有效区分 MDD 样本和对照。这些基因在生物钟途径中显著富集，并与免疫细胞浸润呈强相关性。药物靶点预测表明，小分子如褪黑素和依地普仑可能靶向这些生物钟蛋白。
本研究揭示了与 MDD 密切相关的 4 个关键生物钟基因，它们可能作为诊断生物标志物和治疗靶点。研究结果强调了生物钟紊乱在 MDD 发病机制中的重要作用，为 MDD 的精准诊断和靶向治疗提供了新的见解。
