Exploring causal correlations between inflammatory cytokines and coronary heart disease: A Mendelian randomization...

Coronary heart disease (CHD) is a global health concern, with inflammation significantly contributing to its pathogenesis. It is crucial to understand the relationship between inflammatory cytokines and CHD. This study investigates the causal correlations between circulating inflammatory cytokines and CHD using Mendelian randomization (MR), assessing both causative and resultant roles of these cytokines in CHD. In this bidirectional MR analysis, we used genetic data from a genome-wide association study (GWAS) of 60,801 CHD cases and 123,504 controls of European ancestry. We derived inflammatory cytokine data from a GWAS summary of 14,824 participants. The primary analytical approach was the inverse variance-weighted (IVW) method, supported by MR-Egger, weighted median, and weighted mode analyses. Heterogeneity was assessed using the Cochrane Q test, and horizontal pleiotropy was evaluated through the MR-Egger intercept and the MR-PRESSO global test, ensuring robustness against potential pleiotropic bias. This study pinpointed several cytokines as key upstream influencers on the risk of CHD, including eotaxin (CCL11) (odds ratio [OR]: 1.10, 95% confidence interval [CI]: 1.03-1.18, P = .003), C-C motif chemokine ligand 20 (CCL20) (OR: 1.15, 95% CI: 1.05-1.25, P = .002), macrophage colony-stimulating factor 1 (CSF1) (OR: 1.09, 95% CI: 1.01-1.17, P = .020), Fibroblast growth factor 21 (FGF21) (OR: 1.14, 95% CI: 1.01-1.29, P = .038), Fms-related tyrosine kinase 3 ligand (FLT3LG) (OR: 1.26, 95% CI: 1.09-1.44, P = .001), neurotrophin-3 (NT-3) (OR: 1.12, 95% CI: 1.01-1.24, P = .026), and leukemia inhibitory factor (LIF) (OR: 0.89, 95% CI: 0.80-0.99, P = .029). Conversely, T-cell surface glycoprotein CD5 (CD5) (beta: -0.15, 95% CI: -0.29 to -0.01, P = .042) were identified as downstream factors impacted by CHD. No evidence of heterogeneity or horizontal pleiotropy was detected across all results, and a leave-one-out analysis substantiated the robustness of these findings. These findings suggest that CCL11, CCL20, CSF1, FGF21, FLT3LG, NT-3, and LIF may play a crucial role in the pathogenesis of CHD. Additionally, CHD may impact the expression of CD5. Additional research is needed to explore the potential of these biomarkers in the prevention and treatment of CHD.