Why is this work important?

Trauma patients is prone to a number of complications, the most significant of which is deep vein thrombosis (DVT), which can lead to a variety of complications, such as post thrombotic syndrome, recurrent DVT, and life-threatening pulmonary embolism (PE)^1,2. Post-traumatic DVT (pt-DVT) has long been recognized as one of the most relevant clinical problems in the adult population³, since failure to recognize this common morbidity could lead to an unacceptable rate of PE. It is also a leading cause of morbidity and mortality after trauma^4,5. Because traumatic bone fractures are a major public health issue in China⁶ and the incidence of pt-DVT can reach up to 40%^7-10, which makes pt-DVT a serious threat for public health in China.

The diagnosis of DVT in patients with fractures including laboratory measures of D-dimer (D-D) and ultrasonography. However, D-D levels can be elevated with advanced age, infection, chronic inflammation, cancer, and other conditions, and have relatively low specificity for the diagnosis of DVT. In addition, ultrasonography can only detect patients with DVT who have significant hemodynamic changes as well as imaging features that do not allow for diagnosis and prognosis of thrombosis in its early stages. In order to effectively prevent DVT during the treatment of fracture patients, we usually evaluate patients for thrombosis or administer anticoagulants on admission. However, according to our clinical statistics, existing thrombus assessment models showed poor sensitivity and specificity, and the use of anticoagulants may increase the risk of bleeding in trauma patients. In the face of the existing clinical dilemma of pt-DVT, we need to identify new biomarkers and causative risk factors in fracture patients with DVT, and to provide a deeper and broader understanding of the pathogenesis and prediction of pt-DVT.

What did we discover?

To address these issues, we comprehensively analyzed the metabolic alterations and hematological characteristics of 680 patients with and without pt-DVT by integrating plasma metabolomics, proteomics, and clinical phenotypes from a population of fracture patients. We first analyzed systematic metabolomics and clinical phenotyping data on 580 (pt-DVT: Controls = 252:328) fracture patients, and identified 28 metabolites and 2 clusters of clinical parameters (CPs) associated with pt-DVT. Based on identified metabolites and CPs associated with pt-DVT, we developed a predictive model containing 9 metabolites, and evaluated their generalization ability in an independent cohort (pt-DVT: Controls = 50:50). This result contributes to the early prevention of pt-DVT. Then, the results of pathway analyses demonstrated that multiple energy metabolic pathway such as pyruvate metabolism, TCA cycle, and glycolysis/glycolysis triggered by elevated pyruvate were found to be up-regulated in pt-DVT. Additionally, the decreasing level of red blood cell (RBC) in pt-DVT is also associated with multiple energy metabolic pathways including the TCA cycle, glycolysis/glycolysis, and pyruvate metabolism. To get insight into these metabolic changes, we performed proteomic analysis of 183 patients with fracture patients (pt-DVT: Controls = 96:87) and identified 214 pt-DVT-related proteins. The pathway enrichment of these proteins also involved the glycolysis/glycolysis pathway, which is consistent with the results of metabolism. By this point in the study, keywords such as pyruvic acid, glycolysis/glycolysis, and RBC had stirred our sensitive nerves. Glycolysis/gluconeogenesis-TCA cycle cascaded by pyruvic acid is a major source generating nicotinamide adenine dinucleotide (NADH), which plays a crucial role in the cellular redox status¹¹. After reviewing the references, we found that reactive oxygen species (ROS) in RBCs will alter erythrocyte membrane structure and be enhanced in thrombosis^12-14. Consistent with this hypothesis, our data indicated that ROS-related peroxiredoxins were slightly disturbed, with PRDX5 upregulated and PRDX2 downregulated in pt-DVT. After adding ROS to the keywords, we quickly sketched out the possible regulatory mechanisms of pt-DVT (Figure 1).

Combining metabolomics and proteomics data, we found that most differential proteins in glycolysis/gluconeogenesis pathway were significantly correlated with PRDX5. In addition, lactate dehydrogenases (LDHA/LDHB), the most significantly changed proteins in glycolysis/gluconeogenesis, were reported to be involved in ROS production in variety of cells ^15,16. All these findings can be proposed that the upregulation of glycolysis/gluconeogenesis-TCA cycle cascaded by pyruvic acid may be associated with the accumulation of ROS in RBCs thereby enhance thrombosis, suggesting that intervention in this process may be a potential therapeutic strategy for pt-DVT.

What are our conclusions?

In two independent trauma cohorts, we identified a set of 28 metabolites and 14 CPs as potential biomarkers of pt-DVT, revealing the metabolic and hematological alterations in pt-DVT. Beyond that, we developed a panel of biomarkers including 9 metabolites to distinguish pt-DVT patients efficiently using a machine learning algorithm, suggesting the potential clinical use of an early diagnostic test in pt-DVT. Finally, data resulting from integrative metabolomics and proteomic analyses indicated that the upregulation of glycolysis/gluconeogenesis-TCA cycle cascaded by pyruvic acid may be related to ROS in RBCs, thus enhancing thrombosis.

What are the challenges?

Conducting such a comprehensive metabolomic, proteomic and phenotypic analyses presented several challenges, especially in the sample collection phase and in integrating information from different data dimensions. For the sample recruitment, our team had a careful and clear division of labor. This process spanned four years, through the difficult years of the COVID-19 epidemic, which undoubtedly posed a great challenge to the conduct of our work and delayed its completion from the planned date. After acquiring multi-omics data, we navigated these complexities by employing robust statistical and bioinformatics techniques, ensuring the reliability of the findings. Additionally, the combination of multi-omics insights and the extraction of key information requires a solid knowledge base and access to a large number of papers. Our findings underscored the importance of interdisciplinary approaches in understanding pt-DVT.

What’s Next?

Looking forward, we aim to validate our predictive model in larger, independent cohorts, and enhance our understanding of the metabolic process’ roles in pt-DVT through experimental methods. Further exploration of glycolysis/gluconeogenesis-TCA cycle cascaded by pyruvic acid regulatory mechanisms and its impact on accumulation of ROS in RBCs thereby enhance thrombosis is also on the horizon. Ultimately, this research lays the groundwork for developing new diagnostic tools and therapeutic strategies for pt-DVT.

References:

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