UNASSIGNED: The Genome-Wide Association Study (GWAS) database was used for our analysis. We gathered data on inflammation-related genetic variation from three GWASs of human cytokines. These proteins included 91 circulating inflammatory proteins, tumor necrosis factor-alpha (TNF-α), macrophage inflammatory protein 1b (MIP-1b), and CXC chemokine 13 (CXCL13). The PHN dataset was obtained from the FinnGen biobank analysis round 5, and consisted of 1,413 cases and 275,212 controls. We conducted a two-sample bidirectional MR study using the TwoSampleMR and MRPRESSO R packages (version R.4.3.1). Our main analytical method was inverse variance weighting (IVW), and we performed sensitivity analyses to assess heterogeneity and pleiotropy, as well as the potential influence of individual SNPs, to validate our findings.
UNASSIGNED: According to our forward analysis, five circulating inflammatory proteins were causally associated with the development of PHN: interleukin (IL)-18 was positively associated with PHN, and IL-13, fibroblast growth factor 19 (FGF-19), MIP-1b, and stem cell growth factor (SCF) showed reverse causality with PHN. Conversely, we found that PHN was closely associated with 12 inflammatory cytokines, but no significant correlation was found among the other inflammatory factors. Among them, only IL-18 had a bidirectional causal relationship with PHN.
UNASSIGNED: Our research advances the current understanding of the role of certain inflammatory biomarker pathways in the development of PHN. Additional verification is required to evaluate the viability of these proteins as targeted inflammatory factors for PHN-based treatments.
■全基因组关联研究(GWAS)数据库用于我们的分析。我们从三种人类细胞因子GWAS中收集了炎症相关遗传变异的数据。这些蛋白质包括91个循环炎症蛋白,肿瘤坏死因子-α(TNF-α),巨噬细胞炎性蛋白1b(MIP-1b),和CXC趋化因子13(CXCL13)。PHN数据集从FinnGen生物样本分析第5轮获得,包括1,413例和275,212例对照。我们使用TwoSampleMR和MRPRESSOR软件包(R.4.3.1版)进行了双样本双向MR研究。我们的主要分析方法是方差逆加权(IVW),我们进行了敏感性分析来评估异质性和多效性,以及个体SNP的潜在影响,来验证我们的发现。
■根据我们的前瞻性分析,5种循环炎性蛋白与PHN的发生发展有因果关系:白细胞介素(IL)-18与PHN呈正相关,和IL-13,成纤维细胞生长因子19(FGF-19),MIP-1b,干细胞生长因子(SCF)与PHN呈反向因果关系。相反,我们发现PHN与12种炎症细胞因子密切相关,但其他炎症因子间无明显相关性。其中,只有IL-18与PHN有双向因果关系。
■我们的研究促进了目前对某些炎症生物标志物途径在PHN发展中的作用的理解。需要额外的验证来评估这些蛋白质作为基于PHN的治疗的靶向炎症因子的活力。