ArticleLipids in health and disease2026
Serum YB-1 links dyslipidemia to NET-mediated vascular calcification in hemodialysis.
Article in Lipids in health and disease, 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
backgroundVascular calcification (VC) is highly prevalent in patients undergoing maintenance hemodialysis (MHD) and is associated with cardiovascular morbidity. However, traditional lipid and mineral markers have limited predictive value. Y-box binding protein-1 (YB-1), a regulator of lipid metabolism and inflammation, may provide additional mechanistic and clinical insight.
methodsSerum YB-1 was measured in 209 MHD patients (30-month follow-up) who were stratified into hyperlipidemia and control groups. Receiver Operating Characteristic (ROC) and decision curve analysis (DCA, threshold range 0.1-0.4) were used to assess the predictive performance of YB-1 against traditional models based on lipid, glucose, and bone metabolism. Mechanistic studies in HL-60-derived neutrophil-like cells and a 5/6 nephrectomized rat model were performed to assess the role of YB-1 in neutrophil extracellular trap (NET) formation and VC.
resultsSerum YB-1 was significantly elevated in hyperlipidemia patients and was independently associated with new-onset VC (AUC 0.707, 95% CI 0.630-0.784). YB-1 outperformed lipid-, glucose-, and bone-based models, providing added net clinical benefit in DCA within the 0.24-0.33 threshold range. Mechanistically, serum levels of citrullinated histone H3 (citH3), a NET marker, were increased in hyperlipidemia patients. In vitro, YB-1 and IS synergistically enhanced neutrophil lipid droplet accumulation and citH3 release, while NET-rich supernatants promoted VSMC calcification. In vivo, IS-treated 5/6 nephrectomy rats displayed elevated YB-1, increased citH3, and aggravated aortic calcification.
conclusionSerum YB-1 is a novel predictor and potential mechanistic mediator of VC in MHD patients. Incorporating YB-1 into existing clinical risk models may support earlier recognition of individuals at elevated cardiovascular risk and inform more effective management strategies to improve long-term health outcomes.
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