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Updated: Jun 24, 2025

Detection of MicroRNA Expression in the Kidneys of Immunoglobulin A Nephropathic Mice
Published on: July 8, 2020
A Mendelian randomization study investigating the causal relationships between inflammation and immunoglobulin A
1Institute of Microcirculation, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China; International Center of Microvascular Medicine, Chinese Academy of Medical Sciences, Beijing, China; Department of Pathology and Pathophysiology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Background:
Immunoglobulin A nephropathy (IgAN) is an autoimmune disease characterized by the production of galactose‑deficient IgA1 (Gd‑IgA1) and the deposition of immune complexes in the kidney. Exploring the landscape of immune dysregulation in IgAN is valuable for pathogenesis and disease treatment. We conducted Mendelian randomization (MR) to assess the causal correlations between inflammation and IgAN.
Methods:
Based on available genetic datasets, we investigated potential causal links between inflammation and the risk of IgAN using two-sample MR. We used genome-wide association study (GWAS) summary statistics of 5 typical inflammation markers, 41 inflammatory cytokines, and 731 immune cell signatures, accessed from the public GWAS Catalog. The primary method employed for MR analysis was Inverse Variance Weighted (IVW). To confirm consistency across results, four supplementary MR methods were also conducted: MR-Egger, Weighted Median, Weighted Mode, and Simple Mode. To assess pleiotropy, we used the MR-Egger regression intercept test and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test. Cochrane's Q statistic was applied to evaluate heterogeneity. Additionally, the stability of the MR findings was verified through the leave-one-out sensitivity analysis.
Results:
This study revealed that interleukin-7 (IL-7) and stem cell growth factor beta (SCGF-β) were possibly associated with the risk of IgAN according to the IVW approach, with estimated odds ratios (OR) of 1.059 (95 % confidence interval [CI] 1.015 to 1.104, P = 0.008) and 1.043 (95 % CI 1.002 to 1.085, P = 0.037). Five immune traits were identified that might be linked to IgAN risk, each with P-values below 0.01, including natural killer T %T cell (OR = 1.058, 95 % CI: 1.020 to 1.097, P = 0.002), natural killer T %lymphocyte (OR = 1.055, 95 % CI: 1.016 to 1.096, P = 0.006), CD25++ CD8+ T cell %T cell (OR = 1.057, 95 % CI: 1.016 to 1.099, P = 0.006), CD3 on effector memory CD4+ T cell (OR = 1.045, 95 % CI: 1.019 to 1.071, P = 0.001), and CD3 on CD28+ CD45RA+ CD8+ T cell (OR = 1.042, 95 % CI: 1.016 to 1.068, P = 0.001). CD4 on central memory CD4+ T cell might be a protective factor for IgAN (OR = 0.922, 95 % CI: 0.875 to 0.971, P = 0.002). Moreover, IgAN may be implicated in a high risk of elevated granulocyte colony-stimulating factor (G-CSF) (OR = 1.114, 95 % CI 1.002 to 1.239, P = 0.046).
Conclusion:
Our study revealed exposures among typical inflammation markers, inflammatory cytokines, and immune cell signatures that may potentially linked to IgAN risk by MR analysis. This insight may advance our understanding of the etiology of IgAN and support the development of targeted therapeutic strategies.
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