Exploring causal correlations between inflammatory cytokines and systemic lupus erythematosus: A Mendelian randomization

Abstract

ObjectivesPrevious studies have reported that a few inflammatory cytokines have associations with systemic lupus erythematosus (SLE)—for example, IL-6, IL-17, and macrophage inflammatory protein (MIP). This Mendelian randomization was conducted to further assess the causal correlations between 41 inflammatory cytokines and SLE.MethodsThe two-sample Mendelian randomization utilized genetic variances of SLE from a large publicly available genome-wide association study (GWAS) (7,219 cases and 15,991 controls of European ancestry) and inflammatory cytokines from a GWAS summary containing 8,293 healthy participants. Causalities of exposures and outcomes were explored mainly using inverse variance weighted method. In addition, multiple sensitivity analyses including MR-Egger, weighted median, simple mode, weighted mode, and MR-PRESSO were simultaneously applied to strengthen the final results.ResultsThe results indicated that cutaneous T cell-attracting chemokine (CTACK) and IL-17 may be suggestively associated with the risk of SLE (odds ratio, OR: 1.21, 95%CI: 1.04–1.41, p = 0.015; OR: 1.37, 95%CI: 1.03–1.82, p = 0.029). In addition, cytokines including beta nerve growth factor, basic fibroblast growth factor, IL-4, IL-6, interferon gamma-induced protein 10, monokine induced by interferon-gamma, MIP1b, stromal cell-derived factor-1 alpha, and tumor necrosis factor-alpha are suggested to be the consequences of SLE disease (Beta: 0.035, p = 0.014; Beta: 0.021, p = 0.032; Beta: 0.024, p = 0.013; Beta: 0.019, p = 0.042; Beta: 0.040, p = 0.005; Beta: 0.046, p = 0.001; Beta: 0.021, p = 0.029; Beta: 0.019, p = 0.045; Beta: 0.029, p = 0.048).ConclusionThis study suggested that CTACK and IL-17 are probably the factors correlated with SLE etiology, while a couple of inflammatory cytokines are more likely to be involved in SLE development downstream.

Interleukin-6 signaling pathway in Mendelian randomization: A 10-year bibliometric analysis

“…According to the research by Yuan et al, IL-6 signaling pathway inhibition may offer novel approaches to preventing disorders like coronary artery disease, atrial fibrillation, and ischemic stroke. [24] Of course, the IL-6 signaling pathway has also been associated with other diseases, including depression, [16] multiple sclerosis, [25] low back pain, [31] systemic lupus erythematosus, [18] ischemic stroke, [32] rheumatoid arthritis, [17] asthma, [33] etc. Taken together, current research hotspots in this field focuses on the application of Mendelian randomization to investigate the forms of association between IL-6 signaling pathway and cardiovascular, neurological, immunological and inflammatory diseases.…”

“…[15] In recent years, mendelian randomization has been employed much more frequently lately to explore the IL-6 signaling pathway and related diseases. Multiple Mendelian randomization analyses have demonstrated the connection between IL-6 signaling pathway and various disorders, including Depression, [16] rheumatoid arthritis, [17] systemic lupus erythematosus, [18] Breast Cancer, [19] etc. However, to the best of our knowledge, there is currently no systematic analysis and summary in this area.…”

Association of birth weight, childhood obesity, and age at menarche with ovarian function: an integrated Mendelian randomization study and bioinformatics analysis

“…Pooled GWAS data for birth weight (N = 143677), childhood obesity (N = 13848), and age at menarche (N = 182416) were obtained from the study by Horikoshi et al [12] , the Early Growth Genetics (EGG) consortium [13] , and the ReproGen consortium,, respectively [14] . Pooled GWAS data for ovarian dysfunction (N = 119170), and primary ovarian failure (N = 118482) were obtained from the Finngen database.…”

Altered Gut Microbiota as a Potential Risk Factor for two types of anemia: insights from Mendelian randomization analysis

“…The preliminary was performed primarily using the inverse variance weighted (IVW) method [24], which assumes that all IVs are valid and averages the effect estimates of each gene weighted by the inverse of its variance to obtain a composite estimate. Various additional analysis methods were used to assess the robustness and reliability of the results: (1) weighted median, where the estimated effects of different genes on the target trait are summarized as median values, with each gene estimate assigned a different weight [25]; (2) MR-Egger, where a linear relationship is assumed between exposure and outcome, with causal links estimated based on maximum likelihood methods that identify and correct for horizontal pleiotropy[26]; (3)simple mode, relies on a single-step analysis with one or a few genetic variants as instrumental variables, offering a more direct and intuitive approach to infer causality; [27] (4)weighted mode, utilizes a weighted combination of multiple genetic variants as instrumental variables, which lead to more robust and reliable causal estimates, especially in intricate scenarios involving multiple genetic determinants [28].…”