Centre for Sport and Exercise Sciences, University Malaya, Kuala Lumpur 50603, Malaysia.
Department of Biomedical Engineering, Faculty of Engineering, University Malaya, Kuala Lumpur 50603, Malaysia.
Int J Environ Res Public Health. 2022 Mar 11;19(6):3321. doi: 10.3390/ijerph19063321.
This study aimed to investigate the association between complex brain functional networks and the metabolites in urine in subclinical depression. Electroencephalography (EEG) signals were recorded from 78 female college students, including 40 with subclinical depression (ScD) and 38 healthy controls (HC). The phase delay index was utilized to construct functional connectivity networks and quantify the topological properties of brain networks using graph theory. Meanwhile, the urine of all participants was collected for non-targeted LC-MS metabolic analysis to screen differential metabolites. The global efficiency was significantly increased in the α-2, β-1, and β-2 bands, while the characteristic path length of β-1 and β-2 and the clustering coefficient of β-2 were decreased in the ScD group. The severity of depression was negatively correlated with the level of cortisone ( = 0.016, = -0.40). The metabolic pathways, including phenylalanine metabolism, phenylalanine tyrosine tryptophan biosynthesis, and nitrogen metabolism, were disturbed in the ScD group. The three metabolic pathways were negatively correlated ( = 0.014, = -0.493) with the global efficiency of the brain network of the β-2 band, whereas they were positively correlated ( = 0.014, = 0.493) with the characteristic path length of the β-2 band. They were mainly associated with low levels of L-phenylalanine, and the highest correlation sparsity was 0.11. The disturbance of phenylalanine metabolism and the phenylalanine, tryptophan, tyrosine biosynthesis pathways cause depressive symptoms and changes in functional brain networks. The decrease in the L-phenylalanine level may be related to the randomization trend of the β-1 frequency brain functional network.
本研究旨在探讨亚临床抑郁患者脑功能网络与尿液代谢物之间的关联。对 78 名女性大学生进行了脑电图（EEG）信号记录，其中 40 名患有亚临床抑郁（ScD），38 名健康对照（HC）。利用相位延迟指数构建功能连接网络，并用图论方法量化脑网络的拓扑属性。同时收集所有参与者的尿液进行非靶向 LC-MS 代谢分析，以筛选差异代谢物。结果显示，ScD 组的 α-2、β-1 和 β-2 频段的全局效率显著增加，而β-1 和 β-2 的特征路径长度和β-2 的聚类系数降低。抑郁严重程度与皮质酮水平呈负相关（ = 0.016， = -0.40）。代谢途径，包括苯丙氨酸代谢、苯丙氨酸-酪氨酸-色氨酸生物合成和氮代谢，在 ScD 组中受到干扰。这三个代谢途径与脑网络β-2 频段的全局效率呈负相关（ = 0.014， = -0.493），与β-2 频段的特征路径长度呈正相关（ = 0.014， = 0.493）。它们主要与 L-苯丙氨酸水平降低有关，最高相关稀疏度为 0.11。苯丙氨酸代谢和苯丙氨酸、色氨酸、酪氨酸生物合成途径的紊乱导致抑郁症状和功能脑网络的改变。L-苯丙氨酸水平的降低可能与β-1 频段脑功能网络的随机化趋势有关。
