#635 Effect of multi-biomarker panels based on urinary N-terminal osteopontin on prediction of diabetic kidney disease in patients with diabetes mellitus

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Abstract Background and Aims Diabetic kidney disease (DKD), occurs in 20–40% of patients with diabetes mellitus (DM), is the leading cause of end-stage renal disease (ESRD). DKD is a clinical diagnosis mainly based on the persistent albuminuria and reduced estimated glomerular filtration rate (eGFR) [1]. However, increased UACR and reduced eGFR are the final consequences due to DKD, novel biomarkers are critical for predicting DKD development. Osteopontin (OPN) is a profibrotic adhesion phosphoprotein that participates in cell chemotaxis, adhesion, migration, and proliferation, as well as extracellular matrix (ECM) hyperplasia. Hyperglycemia could enhance OPN gene expression through the activation of the renin-angiotensin system (RAS), mTOR pathway, NF-κB, and TGF-β pathway and then cause podocyte injury and ECM hyperplasia. Therefore, OPN upregulation is not only the result of various pathophysiological processes in DKD, but also results in kidney injury. Osteopontin (OPN) could predict incident DKD in DM patients [2], N-terminal OPN (ntOPN) has a stronger profibrotic adhesion effect than full-length OPN. This study aims to reveal the clinical benefit of ntOPN as a potential marker to identify DM patients at high risk of DKD, and establish ntOPN-based diagnostic and forecast models for renal outcomes in DM patients. Method We performed a cross-sectional study of 316 adults with Type 1 DM≥ 5 years or Type 2 DM, then followed by a prospective observational cohort study of 143 adult DM patients without renal involvement at baseline and follow-up for at least one year. During the follow-up period, the primary endpoint was “DKD occurrence”, defined as the presence of one of the following conditions in DM patients [3]: (1) repeat UACR ≥30 mg/g at least 2 of 3 measurements within 3 to 6 months; (2) eGFR <60 mL/min/1.73 m2 for more than three months; (3) renal pathological findings were consistent with DKD. The secondary endpoint was “DKD progression”, which included: (1) eGFR sustained decreased by at least 25%; (2) development of ESRD, and/or need for renal replacement therapy; (3) death from the renal cause. Logistic regression analysis was performed to analyze the relationship between parameters and the events of DKD occurrence and progression. Receiver operator characteristic (ROC) analysis was used to assess the predictive ability of established models for clinical endpoints. Results The median value of urinary ntOPN (UntOPN) was 44.15 ng/ml in the cross-sectional cohort, DKD prevalence was significantly higher in the high UntOPN group than in the low UntOPN group. The ROC curves of UntOPN, urinary neutrophil gelatinase-associated lipocalin (UNGAL), and their combination indicated that both combination and ntOPN alone perform better than UNGAL for DKD diagnosis (Fig. 1A). In the prospective cohort, UntOPN was an independent risk factor and further improved the predictive ability for DKD occurrence and DKD progression than UNGAL (Figs. 1B and 1C). Based on the parameters detected as risk factors for DKD occurrence and progression, we set up a series of multi-biomarker panels for DKD prediction using UntOPN, UNGAL, serum cystatin C, serum creatinine (Scr), UACR, and TCH/HDL-C ratio. Compared with the model of Scr + UACR, the area under ROC curve (AUC) of the six-biomarker model was higher, and also ranked the highest among the six ROC curves in predicting 1-year risk of DKD occurrence and DKD progression (Figs. 1B and 1C). Conclusion Our results showed that urinary ntOPN is associated with DKD development, and elevated urinary ntOPN is an independent predictor for DKD occurrence and progression. Compared with the traditional biomarkers of Scr + UACR, our multi-biomarker models based on urinary ntOPN performed better in predicting DKD development, which could provide more accurate tools for DKD risk prediction, thereby improving the renal prognosis in DM patients.