ArticleScientific reports2026
KNG-1, HSPG and Robo4 reflect hypertension-driven subclinical renal alterations and provide incremental diagnostic value in type 2 diabetic nephropathy.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Diabetic nephropathy (DN), indicated by persistent urinary albumin excretion or albuminuria, is the major cause of end stage renal disease worldwide. Currently albuminuria is considered the best predictor of subsequent development of DN in type 2 diabetic patients, but it is often induced by arterial hypertension or heart failure in older patients as well. Therefore, additional biomarkers are needed to identify diabetic patients at a high risk of developing DN. The aim of the study was to investigate the expression profiles of some serum proteome biomarkers and to demonstrate their association with early renal alterations among type 2 diabetic patients. This study included 300 type 2 diabetic patients with- (200, UACR > 30 mg/gm) and without- (100, UACR < 30 mg/gm) persistent albuminuria in addition to 100 healthy control subjects. Serum expression patterns of KNG-1, HSPG, Robo4 and other biochemical parameters were evaluated in all participants. We also assessed the combined influence of hypertension and albuminuria on these markers, to explore their potential as non-invasive indicators of early renal risk in T2DM. Results suggest that elevated serum KNG-1, HSPG and Robo4 levels in type 2 diabetic patients might reflect a DN progressive pathology due to various mechanisms. The interaction between hypertension and albuminuria significantly alters biomarker levels in a synergistic manner, emphasizing the need for comprehensive management of both conditions in clinical practice. Additionally, findings highlight that serum proteome signature of these biomarkers provide an incremental predictive value when integrated with conventional clinical parameters, as evidenced by the marked improvement in multivariable regression model performance and discriminative accuracy analyses.
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