Abstract
BACKGROUND: Venous thromboembolic diseases pose a serious threat to human health, and their pathogenesis is closely associated with the abnormal activation of neutrophils and neutrophil extracellular traps (NETs). However, the mechanisms underlying the role of NETs in thrombosis related to Hyperhomocysteinemia (hHcy) remain unclear. In this study, we systematically investigated the correlation between NETs and hHcy-associated thrombosis by measuring key NETs markers (myeloperoxidase, MPO; citrullinated histone H3, CitH3) and cell-free DNA (cfDNA) levels. Based on multivariate analysis, we developed and validated a thrombotic risk prediction model integrating clinical indicators and NETs markers, providing novel biomarkers and an assessment tool for early clinical identification of high-risk patients. METHODS: This study consecutively enrolled 394 hHcy patients who visited the Department of Vascular Surgery and Health Examination Center at Weifang People's Hospital between November 2023 and April 2025. The cohort comprised 71 patients in the deep vein thrombosis (DVT) group and 323 in the non-DVT control group. We systematically collected baseline clinical characteristics and laboratory parameters from all participants, with DVT occurrence serving as the primary endpoint. Independent risk factors for DVT were identified through univariate and multivariate logistic regression analyses, which were subsequently used to construct a risk prediction model. To validate model reliability, internal validation was performed using the following approaches: The discriminative ability of the model was evaluated by analyzing the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, calibration curves to assess consistency, and ecision curve analysis to determine clinical utility. These comprehensive validation methods were applied to both training and validation cohnrts to rigorously test the model's predictive performance. RESULT: Laboratory test results revealed significantly elevated levels of NETs-related markers in the peripheral blood of DVT patients, including Myeloperoxidase-Deoxyribonucleic Acid (MPO-DNA), CitH3, cfDNA, and absolute neutrophil count. Multivariate logistic regression analysis confirmed that MPO-DNA (Odds Ratio, OR = 11.58, 95% CI: 3.75-35.73, Probability Value, p < 0.001), CitH3 (OR = 1.11, 95% CI: 1.05-1.17, p < 0.001), cell-free DNA (OR = 1.02, 95% Confidence Interval, 95% CI: 1.01-1.02, p < 0.001), and neutrophil (OR = 1.67, 95% CI: 1.14-2.44, p = 0.008) were all independent risk factors for DVT in hHcy patients. The risk prediction model constructed based on these factors demonstrated excellent discriminative performance, with area under the receiver operating characteristic curve values of 0.93 (95% CI: 0.88-0.99) in the training cohort and 0.96 (95% CI: 0.88-1.00) in the validation cohort. CONCLUSION: This study demonstrates that hHcy-associated thrombosis is significantly correlated with elevated levels of NETs. Based on these findings, we have developed a novel non-invasive thrombotic risk prediction model that can effectively identify high-risk hHcy patients.