Abstract: FR-PO0522
Urinary Proteomic Signatures Distinguish Diabetic Kidney Disease from Diabetes and Healthy Controls
Session Information
- CKM: Clinical - Trials, Epidemiology, and Biomarkers
October 23, 2026 | Location: Exhibit Hall A, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Cardiovascular-Kidney-Metabolic Health
- 602 Cardiovascular-Kidney-Metabolic Health: Clinical
Authors
- Makhammajanov, Zhalaliddin, Nazarbayev University School of Medicine, Astana, Kazakhstan
- Bimurat, Bikadisha, Nazarbayev University School of Medicine, Astana, Kazakhstan
- Kuanshaliyeva, Zhannat, University Medical Center, Astana, Kazakhstan
- Atageldiyeva, Kuralay, Nazarbayev University School of Medicine, Astana, Kazakhstan
- Durmanova, Aigul, University Medical Center, Astana, Kazakhstan
- Gaipov, Abduzhappar, Nazarbayev University School of Medicine, Astana, Kazakhstan
Background
Diabetic kidney disease (DKD), is associated with progressive loss of kidney function and altered urinary protein excretion. We aimed to characterize urinary proteomic profiles and their differential abundance in patients with DKD, diabetes, and in healthy controls (HC).
Methods
Urinary proteomics was conducted in 55 DKD patients, 74 diabetes patients, and 54 HC using diaPASEF on a timsTOF Pro 2 platform. Raw data were processed with DIA-NN for protein identification, and protein abundances were estimated using MaxLFQ-based label-free quantification. Differential abundance between the patient and control group was assessed using MSstats.
Results
Overall, over 4,600 urinary proteins were identified in all participants. The number of detected protein groups was lowest in DKD patients, whereas the summed MaxLFQ intensity increased from 7.5 (7.5–7.6) in diabetes and 7.5 (7.4-7.6) in HC to 7.8 (7.6–8.1) in DKD (P < 0.001) (Table 1).
The most significant differentially abundant proteins in the DKD group compared with the HC group and T2D with CKD are shown in Fig-1.
Conclusion
Urinary proteomic profiles distinguished DKD from both diabetes without kidney disease and healthy controls. DKD was characterized by higher summed urinary protein intensity, increased abundance of inflammatory, transport, and plasma-derived proteins, and reduced abundance of kidney-enriched, tubular, extracellular matrix, and vascular-associated proteins. These findings suggest that urinary proteomics captures disease-specific molecular alterations in DKD beyond those attributable to diabetes alone and can support biomarker discovery for DKD.
Acknowledgment
This study was funded by the Nazarbayev University Collaborative Research Program, grant number 211123CRP1603.
Table 1. General Characteristics of Study Population
| Parameter | HC, n = 54 | T2D w/o CKD, n = 74 | DKD, n = 55 | P value |
| Gender, female | 27 (50%) | 40 (54%) | 32 (58%) | 0.693 |
| Age, years | 32.2 (29.1–47.7) | 54.3 (46.4–59.3) | 54.9 (48.5–60.1) | <0.001 |
| eGFR, mL/min | 104.6 (95.1–116.8) | 97.0 (86.1–104.8) | 72.3 (50.7–102.7) | <0.001 |
| Urine ACR, mg/mmol | 0.3 (0.1–0.6) | 0.7 (0.3–1.0) | 8.5 (5.0–76.3) | <0.001 |
| Detected protein groups, n | 4553 | 4632 | 4498 | - |
| Summed MaxLFQ intensity, log10 | 7.5 (7.4–7.6) | 7.5 (7.5–7.6) | 7.8 (7.6–8.1) | <0.001 |
Fig-1. Differential protein abundance between DKD vs HC and T2D without CKD
Funding
- Government Support – Non-U.S.