Wang Meiti, Jin Guixiang, Cheng Ying, Guan Shi-Yang, Zheng Jinxin, Zhang Shun-Xian
Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shanghai Yangpu Mental Health Center, Shanghai, China.
Front Genet. 2023 Aug 4;14:1242614. doi: 10.3389/fgene.2023.1242614. eCollection 2023.
Inflammatory cytokines disturbance is the main result of immune dysregulation, which is widely described in major depressive disorder (MDD). However, the potential causal relationship between these two factors has not been discovered. Therefore, the purpose of this study was to investigate the causal relationship between inflammatory cytokines and MDD risk by using the two-sample Mendelian randomization (MR) analysis. Two genetic instruments obtained from publicly available gene profile data were utilized for the analysis. We obtained the genetic variation data of 41 inflammatory cytokines from genome-wide association studies (GWAS) meta-analysis of 8293 individuals of Finnish descent. The MDD data, including 135,458 MDD cases and 344,901 controls, were obtained from the Psychiatric Genomics Consortium Database. For the Mendelian randomization (MR) estimation, several methods were employed, namely, MR-Egger regression, inverse-variance weighted (IVW), weighted median, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) methods. A causal relationship was identified between the genetically proxied levels of Interleukin (IL) -18, IL-1β, and Regulated upon activation normal T cell expressed and secreted (RANTES) and the risk of MDD (OR = 0.968, 95%CI = 0.938, 0.998, = 0.036; OR = 0.875, 95%CI = 0.787, 0.971, = 0.012; OR = 0.947, 95%CI = 0.902, 0.995, = 0.03; respectively). However, our Mendelian randomization (MR) estimates provided no causality of MDD on inflammatory cytokines. Our study elucidates the connection between inflammatory cytokines and MDD by using MR analysis, thereby enhancing our comprehension of the potential mechanisms. By identifying these associations, our findings hold substantial implications for the development of more effective treatments aimed at improving patient outcomes. However, further investigation is required to fully comprehend the exact biological mechanisms involved.
炎症细胞因子紊乱是免疫失调的主要结果,这在重度抑郁症(MDD)中已有广泛描述。然而,这两个因素之间的潜在因果关系尚未被发现。因此,本研究的目的是通过使用两样本孟德尔随机化(MR)分析来研究炎症细胞因子与MDD风险之间的因果关系。利用从公开可用的基因谱数据中获得的两种遗传工具进行分析。我们从对8293名芬兰血统个体的全基因组关联研究(GWAS)荟萃分析中获得了41种炎症细胞因子的遗传变异数据。MDD数据包括135458例MDD病例和344901例对照,来自精神基因组学联盟数据库。对于孟德尔随机化(MR)估计,采用了几种方法,即MR-Egger回归、逆方差加权(IVW)、加权中位数和MR-多效性残差和异常值(MR-PRESSO)方法。在白细胞介素(IL)-18、IL-1β和活化后正常T细胞表达和分泌调节因子(RANTES)的遗传代理水平与MDD风险之间确定了因果关系(OR = 0.968,95%CI = 0.938,0.998,P = 0.036;OR = 0.875,95%CI = 0.787,0.971,P = 0.012;OR = 0.947,95%CI = 0.902,0.995,P = 0.03;分别)。然而,我们的孟德尔随机化(MR)估计未显示MDD对炎症细胞因子有因果关系。我们的研究通过使用MR分析阐明了炎症细胞因子与MDD之间的联系,从而加深了我们对潜在机制的理解。通过确定这些关联,我们的发现对开发旨在改善患者预后更有效的治疗方法具有重大意义。然而,需要进一步研究以充分理解所涉及的确切生物学机制。