Correlation Between C4/IgG with Macroproteinuria in Chronic Kidney Disease: A Pilot Study

Abstract

Hao Zhang,1,* Anqi Xu,2,* Xiangxiang Li,3,* Binbin Pan,1 Xin Wan1 1Department of Nephrology, Nanjing First Hospital, Nanjing Medical University, Nanjing, People’s Republic of China; 2Department of Quality Management, Nanjing Red Cross Blood Center, Nanjing, People’s Republic of China; 3Department of Nephrology, Nanjing Yuhua Hospital, Yuhua Branch of Nanjing First Hospital, Nanjing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Binbin Pan; Xin Wan, Department of Nephrology, Nanjing First Hospital, No. 68, Changle Road, Nanjing, Jiangsu, 210006, People’s Republic of China, Tel [phone], Email [email protected]; [email protected] and Objectives: Loss of immunoglobulin G (IgG) is accompanied with proteinuria, especially macroproteinuria. The complement system participates kidney disease resulting in proteinuria. Whether the ratio of complement and IgG is associated with macroproteinuria remains unknown.Design, Setting, Participants and Measurements: A total of 1013 non-dialysis chronic kidney disease (CKD) patients were recruited according to the electrical case records system with 268 patients who endured kidney biopsy. Patients were grouped via the estimated glomerular filtration rate or the levels of proteinuria determination. Biomarkers in different CKD groups or proteinuria groups were compared by one-way ANOVA or independent samples t-test. Pearson or spearman analysis was employed to analyze correlation between clinical indexes. Further, influence factor of macroproteinuria was studied by using binary logistic regression. The ROC curve was performed to explore probable predictive biomarker for macroproteinuria.Results: No significant difference of complement C3 and C4 among CKD1 to CKD5 stages, while higher level of complement C4 in patients with macroproteinuria. Further, C4 had a positive correlation with proteinuria (r=0.255, p=0.006). After adjusted for age, IgA, IgM, triglyceride and HDL, a binary logistic regression model showed lnC4/IgG (OR=3.561, 95% CI 2.196– 5.773, p< 0.01), gender (OR=1.737, 95% CI 1.116– 2.702, p=0.014), age (OR=0.983, 95% CI 0.969– 0.997, p=0.014), and history of diabetes (OR=0.405, 95% CI 0.235– 0.699, p< 0.01) were independent influence factors of macroproteinuria. The area under the ROC curve was 0.77 (95% CI: 0.75– 0.82, p< 0.001) for C4/IgG. The analysis of ROC curves revealed a best cut-off for complement C4 was 0.024 and yielded a sensitivity of 71% and a specificity of 71%. The area under the ROC curve was 0.841 (95% CI: 0.735– 0.946, p < 0.001) for C4/IgG in IgA nephropathy patients. The analysis of ROC curves revealed a best cut-off for complement C4/IgG was 0.026 and yielded a sensitivity of 75% and a specificity of 81.2%. The area under the ROC curve for C4/IgG in CKD1-5 stages were 0.772, 0.811, 0.785, 0.835, 0.674.Conclusion: Complement C4/IgG could be used to predict macroproteinuria.Keywords: complement C4, immunoglobulin G, macroproteinuria, chronic kidney disease, kidney biopsy

Keywords

• complement c4；immunoglobulin g
• macroproteinuria
• chronic kidney disease；kidney biopsy.