Beyond VO2max: Integrated Physiological Phenotyping and Candidate-Gene Analysis of Elite Versus Recreational Endurance Runners

Figures

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  Figure 1. Schematic representation of the data analysis workflow.

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  Figure 2. Maximal oxygen uptake (VO2max) across the four study subgroups. Note. Box plots for elite male (n = 20), elite female (n = 20), control male (n = 20), and control female (n = 20) runners. Boxes represent the interquartile range, horizontal lines within boxes denote group medians, and whiskers extend to the most extreme non-outlier values; open circles indicate outliers beyond 1.5 × IQR. Individual participant data are overlaid as jittered points. Subgroups are identified by the x-axis labels; the figure is presented in grayscale and no color coding is used. Significance brackets: *** p < 0.001; ns = not significant (p ≥ 0.05); comparisons are Tukey HSD post-hoc tests following the two-way ANOVA (competitive status × sex): status F(1, 76) = 101.56, p < 0.001, η2 = 0.572; sex F(1, 76) = 8.05, p = 0.006, η2 = 0.096; status × sex F(1, 76) = 12.41, p < 0.001, η2 = 0.140.

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  Figure 3. Absolute oxygen consumption across submaximal running speeds. Note. Oxygen consumption (mL·min−1) is plotted across speeds of 12 to 15 km·h−1 for elite male (open squares, solid black line; n = 20), elite female (filled circles, dashed black line; n = 20), control male (open triangles, solid gray line; n = 20), and control female (filled inverted triangles, dashed gray line; n = 20) runners. Data points represent group means, vertical error bars show ± 1 SD, and shaded bands show the SD envelope. Triple asterisks (***) indicate speeds at which the main effect of competitive status was significant at p < 0.001.

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  Figure 4. Blood lactate response to incremental running speed. Note. Capillary fingertip blood lactate concentration (mmol·L−1) is plotted across speeds of 10 to 16 km·h−1 for elite male (open squares, solid black line; n = 20), elite female (filled circles, dashed black line; n = 20), control male (open triangles, solid gray line; n = 20), and control female (filled inverted triangles, dashed gray line; n = 20) runners. Data points represent group means, vertical error bars show ± 1 SD, and shaded bands show the SD envelope. Horizontal dashed reference lines indicate the conventional blood lactate concentration at LT1 onset (≈2 mmol·L−1) and the fixed LT2 criterion (4 mmol·L−1) for visual orientation only; thresholds were determined individually by the Dmax method (LT1) and the fixed 4 mmol·L−1 criterion (LT2). Triple asterisks (***) indicate speeds at which the main effect of competitive status was significant at p < 0.001.

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  Figure 5. Genotype-frequency distributions at five endurance-relevant polymorphisms in elite runners versus recreationally trained controls. Note. Bar panels show the relative frequency (%) of each genotype at ACTN3 R577X (rs1815739), VEGFA rs699947, PPARGC1A Gly482Ser (rs8192678), ACE I/D (287-bp intronic insertion), and PPARG Pro12Ala (rs1801282) for pooled elite (n = 20) and pooled recreational control (n = 20) runners. Numeric labels above each bar indicate absolute individual counts per genotype.

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  Figure 6. Principal component analysis of the integrated physiological phenotype. Note. Biplot showing individual scores on the first two principal components from a PCA of the correlation matrix of six physiological variables (VO2max, sign-reversed running economy per kg, sign-reversed body-fat percentage, lean mass, bone mineral density, and body mass). PC1 explains 40.1% of the total variance, and PC2 explains 33.1% (73.2% combined). PC1 separates elite from recreational runners in both sexes; PC2 reflects sex-linked differences in lean and total body mass.