Complement System-Related Biomarkers in Diabetic Nephropathy: A Bioinformatics and Mendelian Randomization Analysis

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Complement System-Related Biomarkers in Diabetic Nephropathy: A Bioinformatics and Mendelian Randomization Analysis

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Co-author 1

Lifang Wei Wei.lifang@fjtcm.edu The Third People’s Hospital Affiliated to Fujian University of Traditional Chinese Medicine Department of Nephrology Fuzhou China *

Co-author 2

Ye Li 43947173@qq.com Fujian University of Traditional Chinese Medicine N/A Fuzhou China -

Co-author 3

Yuhui Lu luyuhui2006@163.com Fujian University of Traditional Chinese Medicine College of Traditional Chinese Medicine Fuzhou -

Co-author 4

Minmin Xu 1148500328@qq.com The Third People’s Hospital Affiliated to Fujian University of Traditional Chinese Medicine Department of Nephrology Fuzhou China -

Co-author 5

Yue Yu 441342063@qq.com The Third People’s Hospital Affiliated to Fujian University of Traditional Chinese Medicine Department of Nephrology Fuzhou -

Co-author 6

Lijie Li 595301494@qq.com The Third People’s Hospital Affiliated to Fujian University of Traditional Chinese Medicine Department of Nephrology Fuzhou China -

Co-author 7

Min Lin mlin2009@163.com The Third People’s Hospital Affiliated to Fujian University of Traditional Chinese Medicine College of Traditional Chinese Medicine Fuzhou China -

Co-author 8

Lifei Fan 593452822@qq.com The Third People’s Hospital Affiliated to Fujian University of Traditional Chinese Medicine College of Traditional Chinese Medicine Fuzhou China -

Co-author 9

Jing Cai caiji1@163.com The Third People’s Hospital Affiliated to Fujian University of Traditional Chinese Medicine Fuzhou China -

Co-author 10

Co-author 11

Co-author 12

Co-author 13

Co-author 14

Co-author 15

Introduction

Diabetic nephropathy (DN) is a major complication of diabetes and a leading cause of end-stage kidney disease. Emerging evidence suggests complement system activation plays a critical role in DN progression. This study aimed to identify complement system-related genes (CSRGs) as potential diagnostic biomarkers and explore their pathogenic role in DN using multi-omics and Mendelian randomization (MR) approaches.

Methods

Transcriptomic data were obtained from GEO datasets (GSE96804, GSE104948), and CSRGs were extracted from the GeneCards database. Differentially expressed CSRGs (DE-CSRGs) were identified through differential gene expression and WGCNA. Machine learning algorithms (Lasso, SVM-RFE, Boruta) were employed to screen candidate genes. A diagnostic nomogram was constructed, and its performance evaluated using calibration and ROC curves. Immune infiltration and checkpoint analysis were conducted, along with GSVA enrichment. MR analysis was performed using eQTL and GWAS summary statistics from the IEU OpenGWAS database to assess causal relationships.

Results

Five biomarkers (CKB, ANXA1, HSPA1L, CYP27B1, and XYLT1) showed consistent expression trends across datasets and were incorporated into a diagnostic nomogram with high predictive accuracy (AUC ~1.0). GSVA revealed OXPHOS pathway activation in CKB, HSPA1L, CYP27B1, and XYLT1, but inhibition in ANXA1. Immune profiling identified 12 significantly altered immune cell types in DN, with strong correlations between biomarkers and immune cell infiltration (e.g., ANXA1 and exhausted T cells, r = 0.62; CKB and exhausted T cells, r = –0.59). ANXA1 was also positively correlated with multiple immune checkpoints. MR analysis demonstrated a significant causal association between HSPA1L and DN (OR = 1.625, 95% CI: 1.272–2.076, P = 9.96×10⁻⁵). Drug prediction and molecular docking identified promising interactions between biomarkers and known compounds (e.g., HSPA1L and carbamazepine, ΔG = –8.9 kcal/mol).

Conclusion

This study identifies five complement system-related genes as potential diagnostic and therapeutic biomarkers in DN. In particular, HSPA1L was confirmed as a genetic risk factor through MR. These findings provide new insight into the complement system’s contribution to DN pathogenesis and suggest promising avenues for diagnostic and therapeutic development.

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