Complement Proteins Identify Rapidly Progressive Diabetic Kidney Disease

Donghwan Yun^{1

2}, Sohyun Bae¹, Yuqian Gao³, Lauren Lopez⁴, Dohyun Han⁵, Carrie D Nicora³, Tae Youn Kim⁶, Kyung Chul Moon⁷, Dong Ki Kim¹, Thomas L Fillmore³, Yon Su Kim^{1

2}, Avi Z Rosenberg⁸, Weijie Wang⁹, Pinaki Sarder¹⁰, Wei-Jun Qian³, Maryam Afkarian¹¹, Seung Seok Han¹

Affiliations

¹ Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.
² Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea.
³ Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA.
⁴ Division of Nephrology, Department of Medicine, University of California, Davis, California, USA.
⁵ Transdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul, Korea.
⁶ School of Nursing, University of California, Davis, Sacramento, California, USA.
⁷ Department of Pathology, Seoul National University College of Medicine, Seoul, Korea.
⁸ Department of Pathology, Johns Hopkins University, Maryland, USA.
⁹ Department of Internal Medicine, University of California, Berkeley, Berkeley, California, USA.
¹⁰ Department of Medicine-Quantitative Health, University of Florida College of Medicine, Gainesville, Forida, USA.
¹¹ Department of Internal Medicine, University of California, Davis, California, USA.

PMID: 40677326
PMCID: PMC12266264
DOI: 10.1016/j.ekir.2025.04.061

Complement Proteins Identify Rapidly Progressive Diabetic Kidney Disease

Donghwan Yun et al. Kidney Int Rep. 2025.

. 2025 May 6;10(7):2296-2310.

doi: 10.1016/j.ekir.2025.04.061. eCollection 2025 Jul.

Authors

Affiliations

¹ Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea.
² Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea.
³ Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA.
⁴ Division of Nephrology, Department of Medicine, University of California, Davis, California, USA.
⁵ Transdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul, Korea.
⁶ School of Nursing, University of California, Davis, Sacramento, California, USA.
⁷ Department of Pathology, Seoul National University College of Medicine, Seoul, Korea.
⁸ Department of Pathology, Johns Hopkins University, Maryland, USA.
⁹ Department of Internal Medicine, University of California, Berkeley, Berkeley, California, USA.
¹⁰ Department of Medicine-Quantitative Health, University of Florida College of Medicine, Gainesville, Forida, USA.
¹¹ Department of Internal Medicine, University of California, Davis, California, USA.

PMID: 40677326
PMCID: PMC12266264
DOI: 10.1016/j.ekir.2025.04.061

Abstract

Introduction: Mechanisms underlying diabetic kidney disease (DKD) progression remain incompletely understood. This study used untargeted and targeted mass spectrometry-based proteomics in 2 independent cohorts to capture rapidly progressive DKD.

Methods: We conducted untargeted and targeted mass spectrometry on urine samples from Korean patients with type 2 diabetes and biopsy-confirmed diabetic nephropathy (SNUH-DN cohort; n = 64) and a DKD subgroup of the Chronic Renal Insufficiency Cohort (CRIC-T2D; n = 282), respectively. Urine proteins associated with kidney disease progression (doubling of serum creatinine, ≥ 50% decrease in estimated glomerular filtration rates [eGFRs], or progression to end-stage kidney disease[ESKD]) were identified after adjusting for eGFR, proteinuria, and other clinical variables.

Results: In the SNUH-DN patients, urine proteins clustered into 2 groups, with cluster 1 exhibiting a 4.6-fold higher hazard of disease progression (95% confidence interval [CI]: 1.9-11.5) than cluster 0. Proteins in cluster 1 mapped to 10 pathways, 4 of the top 5 being complement-related. A high complement score, derived from urine complement protein abundance, correlated with histopathologic features of DKD and conferred a 2.4-fold greater hazard of disease progression (95% CI: 1.0-5.4) than a low complement score. In CRIC-T2D, targeted mass spectrometry similarly confirmed that complement score stratified patients into rapid and slow DKD progression groups. In both cohorts, complement score exhibited a linear association with disease progression.

Conclusion: The strong association between complement activation and rapid DKD progression highlights the need to explore complement inhibition as a potential therapeutic strategy for DKD.

Keywords: biomarkers; complement system proteins; diabetic nephropathies; pathology; proteomics.

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Figures

**Figure 1**
Unsupervised clustering based on untargeted proteomics in the SNUH-DN cohort. (a) Uniform manifold approximation and projection (UMAP) plot with 2 distinct clusters (clusters 0 and 1). (b) Multivariable-adjusted cumulative incidence of kidney disease progression according to clusters, after adjustment for age, sex, body mass index, hypertension, diabetes duration, urine protein-to-creatine ratio, and eGFR. (c) Sankey plot illustrating the relationships among glomerular classes, clusters, and kidney disease progression within 1 year. eGFR, estimated glomerular filtration rate.

**Figure 2**
Complement pathway and kidney disease progression in the SNUH-DN cohort. (a) Pathway analysis of the differentially abundant proteins in cluster 1 compared with cluster 0. (b) Volcano plot of the differentially abundant proteins in cluster 1 compared with cluster 0. The dashed line denotes the threshold of significance. Red and blue dots represent proteins increased and decreased in cluster 1, respectively, compared with cluster 0. (c) Heatmap of urinary complement component abundance categorized by clustering, kidney disease progression within 1 year, and complement function.

**Figure 3**
Complement score and kidney disease progression in the SNUH-DN cohort. (a) Bar plot of complement score in clusters 0 and 1. ∗∗∗P < 0.001. (b) Multivariable-adjusted cumulative incidence of kidney disease progression according to complement score groups after adjustment for age, sex, body mass index, hypertension, diabetes duration, urine protein-to-creatinine ratio, and eGFR. (c) Penalized spline regression according to complement score after adjusting for age, sex, body mass index, hypertension, diabetes duration, urine protein-to-creatinine ratio, and eGFR. eGFR, estimated glomerular filtration rate.

**Figure 4**
Complement score and kidney disease progression in the CRIC-T2D subcohort. (a) Bar plot of complement score in high and low score groups. ∗∗∗P < 0.001. (b) Multivariable-adjusted cumulative incidence of kidney disease progression according to complement score groups after adjustment for age, sex, body mass index, race, hypertension, 24-hour urine protein, and eGFR. (c) Penalized spline regression according to complement score after adjusting for age, sex, body mass index, race, hypertension, 24-hour urine protein, and eGFR. eGFR, estimated glomerular filtration rate.

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Update of

Urine complement proteins are associated with kidney disease progression of type 2 diabetes in Korean and American cohorts.
Yun D, Bae S, Gao Y, Lopez L, Han D, Nicora CD, Kim TY, Moon KC, Kim DK, Fillmore TL, Kim YS, Rosenberg AZ, Wang W, Sarder P, Qian WJ, Afkarian M, Han SS. Yun D, et al. medRxiv [Preprint]. 2024 Aug 17:2024.08.15.24312080. doi: 10.1101/2024.08.15.24312080. medRxiv. 2024. Update in: Kidney Int Rep. 2025 May 06;10(7):2296-2310. doi: 10.1016/j.ekir.2025.04.061. PMID: 39211860 Free PMC article. Updated. Preprint.

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Complement Proteins Identify Rapidly Progressive Diabetic Kidney Disease

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Complement Proteins Identify Rapidly Progressive Diabetic Kidney Disease

Authors

Affiliations

Abstract

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Update of

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