Predicting the Metabolic Biomarkers Associated With Injury in Athletes

Predicting the Metabolic Biomarkers Associated With Injury in Athletes

For elite athletes, sports injuries significantly impede the further enhancement of their competitive performance. Consequently, the significance of preventing, detecting, and addressing potential injury issues has become increasingly critical. Currently, the comprehensive evaluation of athletes' physical function and condition primarily depends on a range of physiological, biochemical, and immunological indicators. However, these methods have progressively exposed their limitations. As an advanced bioinformatics technology, omics research demonstrates unique advantages. By leveraging multi-omics research and analysis, it is possible to more accurately observe the physiological and biochemical changes that athletes undergo during training and competition, as well as their regulatory mechanisms. This approach can provide practical data, identify biomarkers that can warn of potential injuries, and offer precise guidance for training monitoring and injury prevention. It also provides a foundation for developing diverse, precise, and personalized sports programs and rehabilitation plans.

Investigators will collect fasting venous blood. White blood cell count, red blood cell count, erythrocyte specific volume, hemoglobin, C-reactive protein, procalcitonin, erythrocyte sediment rate, lactic acid,creatine kinase, liver function indicators, blood urea, blood creatinine, blood uric acid, blood testosterone, blood cortisol, immunoglobulin (IgG, IgA, IgM) and ferritin levels were measured. The levels of IL-2, IL-6, IL-1β and TNF-α were determined by ELISA. Blood samples were purified and analyzed by proteomics, metabolomics and lipidomics methods. Urine and stool samples were collected and analyzed by multi-omics method.

Inclusion Criteria:

1. Age： Athletes 12-30 years old
2. Acute injury during exercise: such as muscle, sprain, contusion, torn ligament, dislocation, fracture.

Exclusion Criteria:

1. Athletes with serious cardio-cerebrovascular disease and abnormal liver and kidney function
2. Recent use of drugs or supplements that affect metabolism.
3. Pregnancy, lactation or special conditions that may affect metabolism.