Department of Neuropharmacology, Beijing Neurosurgical Institute, Capital Medical University, No. 119 South Fourth Ring West Road, Fengtai District, Beijing, 100070, China.
Department of Pain Management, The First Affiliated Hospital, Zhengzhou University, Henan, China.
Sci Rep. 2024 Jul 26;14(1):17657. doi: 10.1038/s41598-024-67615-4.
Stroke, the second leading cause of death and disability, causes massive cell death in the brain followed by secondary inflammatory injury initiated by disease associated molecular patterns released from dead cells. Nonetheless, the evidence regarding the causal relationship between inflammatory cytokines and stroke subtypes is obscure. To leverage large scale genetic association data to investigate the interplay between circulating cytokines and stroke, we adopted a two-sample bi-directional Mendelian randomization (MR) analysis. Firstly, we performed a forward MR analysis to examine the associations of genetically determined 31 cytokines with 6 stroke subtypes. Secondly, we conducted a reverse MR analysis to check the associations of 6 stroke subtypes with 31 cytokines. In the forward MR analysis, genetic evidence suggests that 21 cytokines were significantly associated with certain stroke subtype risk with |β| ranging from 1.90 × 10 to 0.74. In the reverse MR analysis, our results found that five stroke subtypes (intracerebral hemorrhage (ICH), large artery atherosclerosis ischemic stroke (LAAS), lacunar stroke (LS), cardioembolic ischemic stroke (CEI), small-vessel ischemic stroke (SV)) caused significantly changes in 16 cytokines with |β| ranging from 1.08 × 10 to 0.69. In particular, those five stroke subtypes were statistically significantly associated with C-reactive protein (CRP). In addition, ICH, LAAS, LS and SV were significantly correlated with vascular endothelial growth factor (VEGF), while LAAS, LS, CEI and SV were significantly related to fibroblast growth factor (FGF). Moreover, integrated bi-directional MR analysis, these factors (IL-3Rα, IL-6R, IL-6Rα, IL-1Ra, insulin-like growth factor-1(IGF-1), IL-12Rβ2) can be used as predictors of some specific stroke subtypes. As well as, IL-16 and C-C motif chemokine receptor 7 (CCR7) can be used as prognostic factors of stroke. Our findings prognostic identify potential pharmacological opportunities, including perturbation of circulating cytokines for both predicting stroke risk and post stroke treatment effects. As we conducted a comprehensive search and analysis of stroke subtype and cytokines in the existing publicly available GWAS database, the results have good population-generalizability.
中风是第二大致死和致残原因，它会导致大脑大量细胞死亡，随后由死亡细胞释放的疾病相关分子模式引发继发性炎症损伤。尽管如此，关于炎症细胞因子与中风亚型之间的因果关系的证据仍不明确。为了利用大规模遗传关联数据来研究循环细胞因子与中风之间的相互作用，我们采用了两样本双向孟德尔随机化（MR）分析。首先，我们进行了正向 MR 分析，以研究 31 种细胞因子与 6 种中风亚型之间的关联。其次，我们进行了反向 MR 分析，以检查 6 种中风亚型与 31 种细胞因子之间的关联。在正向 MR 分析中，遗传证据表明，21 种细胞因子与某些中风亚型的风险显著相关，|β|值范围从 1.90×10至 0.74。在反向 MR 分析中，我们的结果发现，5 种中风亚型（脑内出血 (ICH)、大动脉粥样硬化性缺血性中风 (LAAS)、腔隙性中风 (LS)、心源性栓塞性缺血性中风 (CEI)、小血管性缺血性中风 (SV))导致 16 种细胞因子发生显著变化，|β|值范围从 1.08×10至 0.69。特别是，这 5 种中风亚型与 C 反应蛋白（CRP）显著相关。此外，ICH、LAAS、LS 和 SV 与血管内皮生长因子（VEGF）显著相关，而 LAAS、LS、CEI 和 SV 与成纤维细胞生长因子（FGF）显著相关。此外，通过综合双向 MR 分析，这些因素（IL-3Rα、IL-6R、IL-6Rα、IL-1Ra、胰岛素样生长因子-1（IGF-1）、IL-12Rβ2）可作为某些特定中风亚型的预测因子。同样，IL-16 和 C-C 基序趋化因子受体 7（CCR7）可作为中风的预后因子。我们的研究结果为潜在的药物治疗机会提供了预测指标，包括通过干扰循环细胞因子来预测中风风险和中风后的治疗效果。由于我们在现有的公开 GWAS 数据库中对中风亚型和细胞因子进行了全面的搜索和分析，因此结果具有良好的人群普遍性。
