Abstract: FR-PO1204
Novel Kidney-Specific Biomarker Panel Accurately Distinguishes Lupus Nephritis from Diabetic Kidney Disease Through Distinct Molecular Pathways
Session Information
- CKD: Mechanisms, AKI, and Beyond - 2
November 07, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2303 CKD (Non-Dialysis): Mechanisms
Authors
- Nerenberg, Mike, Exagen Inc, Vista, California, United States
- Taghavi, Sepehr, Exagen Inc, Vista, California, United States
- Silva, Ines A, Exagen Inc, Vista, California, United States
- O'Malley, Tyler, Exagen Inc, Vista, California, United States
- Kyttaris, Vasileios C, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States
Background
Lupus nephritis (LN) and diabetic kidney disease (DKD) are major causes of chronic kidney disease needing early diagnosis. Conventional markers (serum creatinine, eGFR) detect damage late. We hypothesized a panel of kidney-specific plasma proteins (UMOD, MIOX, HPSE, AREL1) could detect early LN and DKD and reflect distinct disease pathways.
Methods
UMOD, MIOX, HPSE, AREL1 were measured by ELISA in plasma from DKD (type 1 & 2 combined, n=99), LN (biopsy-confirmed, n=31), and matched apparently healthy volunteers (AHV, n=130). Multiclass logistic regression classified AHV, DKD, and LN; performance assessed by ROC (one-vs-rest), confusion matrix, and predicted probabilities. Pathway (KEGG) and protein-interaction (STRING) analyses explored functional roles. Data from PERL and FIND were provided by NIDDK CR.
Results
Panel yielded strong discrimination: AUC=0.99 LN, AUC=0.89 DKD, AUC=0.88 AHV, clearly separating classes. LN had lower UMOD, MIOX; higher HPSE, AREL1 vs DKD/AHV (p<0.001). DKD showed reduced HPSE, elevated MIOX vs AHV. Functional analyses linked biomarkers to renal-specific pathways: tubular function (MIOX, UMOD), matrix remodeling (HPSE), and proteasomal degradation (AREL1).
Conclusion
The four-protein panel reliably detects and differentiates DKD and LN, significantly outperforming standard measures and providing insight into distinct disease mechanisms.
Demographics
| Total (N=260) | AHV DKD Matched (N=99) | DKD (N=99) | AHV LN Matched (N=31) | LN (N=31) | |
| Subject is Female - n(%) | 146 (56%) | 47 (47%) | 47 (47.5%) | 26 (84%) | 26 (84%) |
| Subject is White - n(%) | 116 (45%) | 47 (47%) | 47 (47.5%) | 11 (35%) | 11 (35%) |
| Age - Mean (SD) | 51.4 (14.1) | 56.6 (11.0) | 56.6 (11.0) | 34.7 (9.5) | 35.0 (9.8) |
| eGFR - Mean (SD) | 71.7 (35.5) | 86.6 (22.7) | 43.1 (32.6) | 88.0 (16.6) | 99.3 (30.5) |
Funding
- Commercial Support – Exagen Inc.