Identification of the serum metabolomic profile for acute ischemic preconditioning in athletes

Abstract

Purpose: In recent years, ischemic preconditioning (IPC) has emerged as an effective strategy to increase tissue resistance against long-term ischemic damage and has been increasingly integrated into exercise regimens. However, further research is needed to explore the impact of IPC-mediated metabolic alterations from an exercise standpoint to conduct a comprehensive exploration of metabolic alterations and their exercise-related mechanisms during acute IPC.

Methods: Nontarget metabolomics was performed on blood samples obtained from 8 male athletes both before and after IPC. The studies included the identification of differentially abundant metabolites, analysis of receiver operating characteristic (ROC) curves, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for differentially abundant metabolites, and metabolite set enrichment analysis (MSEA).

Results: Nineteen differentially abundant metabolites were identified, with increasing levels of five metabolites, such as O-desmethyltramadol and D-gluconate, whereas 14 metabolites, including 9-hydroxy-10e, 12z-octadecadienoic acid (9-HODE), tetradione, 2-hexenal, (2,4-dichlorophenoxy)acetic acid (2,4-D), and phosphatidylserine (PS), decreased. ROC curve analysis revealed an AUC of 0.9375 for D-gluconate. Both KEGG enrichment analysis and MSEA revealed enrichment in the pentose phosphate pathway (PPP).

Conclusion: This study revealed that PPP, D-gluconate, O-desmethyltramadol, and D-2-aminobutyric acid could be upregulated within 5 min after acute IPC, whereas 2,4-D, PS, 9-HODE, 2-hexenal, and tetradinone could be downregulated. These identified metabolites show promise for improving physical functional status and could be harnessed to enhance athletic performance.

Keywords: D-gluconate; ischemic preconditioning; metabolomic profile; pentose phosphate pathway; taekwondo athletes.

FIGURE 1

Experimental protocol for the study. The rectangle above the timeline represents the intervention for the left leg, and the rectangle below represents the intervention for the right leg. The red rectangle represents a pressure of 220 mmHg, whereas the blue rectangle represents a pressure of 0 mmHg. Each rectangle corresponds to a duration of 5 min, and the experiment proceeds from left to right.

FIGURE 2

Data quality control and sample correlation. (A) Three-dimensional PCA plots demonstrating the metabolic variations within and between sample groups. Enhanced method stability and data quality are indicated by minimal differences among QC samples. The dense distribution of QC samples on the three-dimensional PCA chart ensures data reliability. (B) Sample correlation analysis was used to quantify and assess alterations in metabolite composition and abundance across samples via correlation data. A correlation value approaching 1 signifies a strong resemblance in metabolic composition and abundance among samples.

FIGURE 3

Differentially abundant metabolite identification. (A) Combining orthogonal signal correction (OSC) and PLS-DA simplifies the model, enhances explanatory power, and maintains predictive ability. This method optimizes the ability to distinguish between Group (A) and Group (B). The VIP value in OPLS-DA is used to identify important metabolites, with a VIP value greater than 1 indicating significance. (B) Statistical chart of differential metabolism upregulation and downregulation in positive and negative ion modes. (C) The x-axis shows the VIP value, the y-axis lists the differentially abundant metabolites, and the color legend indicates the abundance in different groups; red indicates upregulation, and green indicates downregulation. A higher VIP value indicates a stronger contribution to group distinction, with metabolites having a VIP value above 1 showing significant differences. (D) The x-axis depicts the log2-fold difference in metabolite abundance for each control group, whereas the y-axis illustrates the −log10 of the P-value after the T-test. The dashed line perpendicular to the y-axis indicates the P-value threshold for screening differentially abundant metabolites. Red dots indicate upregulated differentially abundant metabolites (FC > 1) with VIP ≥ 1 and P < 0.05, whereas blue dots represent downregulated differentially abundant metabolites (FC < −1) with VIP ≥ 1 and P < 0.05. The size of the dots corresponds to the VIP value of the metabolite. (E) Differentially abundant metabolite correlation heatmap. Positive correlations are depicted by dark blue shading, which approaches 1, whereas negative correlations are shown by dark red shading, which approaches −1. The color gradient below the heatmap illustrates the Pearson correlation coefficient between the two differentially abundant metabolites. (F) In the heatmap, each row represents a metabolite, and each column represents a sample. The color intensity reflects the abundance of the metabolite, with red indicating higher abundance and blue indicating lower abundance. The differentially abundant metabolites presented diverse accumulation patterns between group (A) and group (B).

FIGURE 4

ROC analysis of differentially abundant metabolites. The ROC curve analysis on the left was utilized to assess the accuracy of the metabolites as biomarkers. The x-axis represents the 1-specificity value, whereas the y-axis represents the sensitivity value. The AUC value, which indicates the area under the curve, is employed to determine the accuracy of a species as a biomarker. AUC = 0.5 ∼ 0.7 signifies lower accuracy, AUC = 0.7 ∼ 0.9 indicates moderate accuracy, and higher accuracy is achieved with AUC values above 0.9. The circle plot on the right displays the top 10 differentially abundant metabolites with corresponding AUC values. Each circle represents a specific metabolite, and the proximity of the circle to 270° indicates a higher AUC value closer to 1.

FIGURE 5

KEGG enrichment analysis of differentially abundant metabolites. (A): Visualization of the distribution of metabolites across various KEGG pathway classifications, highlighting metabolism as the most prevalent category. The x-axis denotes the number of metabolites, whereas the y-axis indicates pathway classification. (B): The ordinate represents the pathway, and the abscissa shows the percentage of pathways as a proportion of all differentially abundant metabolites. Darker colors indicate smaller Q values, with each column displaying the number of pathways and their corresponding Q value. A Q value less than 0.05 after multiple testing correction indicates significant pathway enrichment. The Q value represents the p-value after FDR correction. (C): The KEGG enrichment circle plot shows differentially abundant metabolites in different pathways. The first circle depicts the enriched pathway, with an external coordinate ruler indicating the number of differentially abundant metabolites. Various colors represent distinct KEGG A classes. The second circle represents the number of pathways and Q values in the background, with longer bars indicating more differentially abundant metabolites and redder colors indicating smaller Q values. The third circle presents a bar chart displaying the proportion of up- and downregulated metabolites, with dark purple denoting upregulated metabolites and light purple denoting downregulated metabolites. The fourth circle illustrates the RichFactor value for each pathway, with grid lines representing increments of 0.1. (D): This image displays a KEGG enrichment bubble chart illustrating enriched pathways. The y-axis represents pathways, whereas the x-axis represents the enrichment factor (the ratio of differentially abundant metabolites in the pathway to all quantities in the pathway). The size of the bubbles indicates the significance, with redder colors indicating smaller Q values. (E): The chart depicts differences in KEGG enrichment, with the y-axis showing −log10 (Q value) and the x-axis representing the z score value (the difference between upregulated and downregulated metabolites as a proportion of total differentially abundant metabolites). The yellow line signifies a Q value threshold of 0.05. The right side of the image displays the top 20 pathways on the basis of the Q values, with different colors representing different classes.

FIGURE 6

Metabolite set enrichment analysis plot. The enriched pathways in the metabolic set are listed on the left side. The length of each column represents the degree of enrichment, whereas the color indicates the p-value. Please sort the pathways according to the p-value, from smallest to largest.