Mental Health Center of Weifang City, No. 8899, Wei'an Road, High-tech Zone, Weifang, 26100, Shandong Province, People's Republic of China.
School of Clinical Medicine, Weifang Medical University, Weifang, People's Republic of China.
Sci Rep. 2024 Jan 20;14(1):1821. doi: 10.1038/s41598-024-52442-4.
As research progresses, the intricate metabolic connections between depression and tryptophan, as well as kynurenine (KYN), have become increasingly evident. In studies investigating the relationship between KYN and depression, the conclusions reached thus far have been inconsistent. Therefore, we propose employing a two-sample mendelian randomization (MR) approach to further elucidate the relationship between KYN and depression. We utilized extensive data from large-scale genome-wide association studies to identify single nucleotide polymorphisms that act as instrumental variables for kynurenine and depression in European ancestry populations, ensuring compliance with MR assumptions. We employed five MR algorithms, namely, weighted median, MR-Egger, inverse variance weighted (IVW), simple mode, and weighted mode, with IVW as the primary analysis method. Sensitivity tests were conducted using Cochran's Q test, MR-Egger intercept test, MR Pleiotropy Residual Sum and Outlier, and Leave-one-out analysis.The IVW analysis revealed that each standard deviation increase in kynurenine corresponded to a 1.4-fold increase in the risk of depression (OR = 1.351, 95% CI 1.110-1.645, P = 0.003). The direction of the effect size (positive or negative) was consistent with the findings from the other four algorithms. Sensitivity tests indicated no heterogeneity or horizontal pleiotropy among the instrumental variables. Elevated levels of kynurenine have a causal relationship with an increased risk of developing depression.
随着研究的进展,抑郁与色氨酸以及犬尿氨酸(KYN)之间复杂的代谢联系变得越来越明显。在研究 KYN 与抑郁之间关系的过程中,迄今为止得出的结论并不一致。因此,我们建议采用两样本 Mendelian 随机化(MR)方法来进一步阐明 KYN 与抑郁之间的关系。我们利用来自大规模全基因组关联研究的广泛数据,确定了在欧洲血统人群中作为犬尿氨酸和抑郁的工具变量的单核苷酸多态性,以确保符合 MR 假设。我们使用了五种 MR 算法,即加权中位数、MR-Egger、逆方差加权(IVW)、简单模式和加权模式,其中 IVW 是主要分析方法。使用 Cochran's Q 检验、MR-Egger 截距检验、MR 多效性残差总和和异常值以及单样本剔除分析进行了敏感性测试。IVW 分析表明,犬尿氨酸每增加一个标准差,抑郁的风险就会增加 1.4 倍(OR=1.351,95%CI 1.110-1.645,P=0.003)。效应大小的方向(正或负)与其他四种算法的结果一致。敏感性测试表明,工具变量之间没有异质性或水平多效性。犬尿氨酸水平升高与抑郁风险增加有因果关系。