Influence of Genetic Polymorphisms and Biochemical Biomarkers on Response to Nutritional Iron Supplementation and Performance in a Professional Football Team: A Pilot Longitudinal Study.

BACKGROUND

Iron deficiency is a prevalent issue among elite athletes, particularly in endurance-based sports like football, where optimal iron status is crucial for aerobic capacity and performance. Despite the well-documented role of iron in oxygen transport and energy metabolism, the interplay between genetic polymorphisms, biochemical markers, and iron supplementation remains poorly understood. This study aimed to investigate the relationship between genetic polymorphisms and iron status in professional football players, assess the impact of iron supplementation on athletic performance, and develop a predictive model for iron supplementation based on genetic and biochemical profiles.

METHODS

A longitudinal study was conducted over three seasons (2021-2024) with 48 male professional football players. Participants underwent genotyping for polymorphisms in (rs4646994), ACTN3 (rs1815739), (rs17602729), (rs8111989), (rs1799945), and (rs2700352, rs28497577). Biochemical markers (ferritin, haemoglobin, haematocrit, serum iron) and performance metrics (GPS-derived data) were monitored. Iron supplementation (105 mg/day ferrous sulphate) was administered to players with ferritin <30 ng/mL. A Total Genotype Score (TGS) was calculated to evaluate genetic predisposition.

RESULTS

Players with "optimal" genotypes ( DD, CC, CC, GC) required less iron supplementation (TGS = 51.25 vs. 41.32 a.u.; = 0.013) and exhibited better performance metrics. Iron supplementation significantly improved haemoglobin and haematocrit in deficient players ( < 0.05). The TGS predicted supplementation need (AUC = 0.711; = 0.023), with a threshold of 46.42 a.u. (OR = 5.23, 95% CI: 1.336-14.362; = 0.017 for non-supplemented players). Furthermore, performance data revealed that iron-supplemented players had significantly lower competition time (1128.40 vs. 1972.84 min; = 0.003), total distance covered (128,129.42 vs. 218,556.64 m; = 0.005), and high-speed running in the 18-21 km/h (7.58 vs. 10.36 m/min; = 0.007) and 21-24 km/h (4.43 vs. 6.13 m/min; = 0.010) speed zones. They also started fewer matches (11.50 vs. 21.59; < 0.001).

CONCLUSIONS

Genetic profile combined with biochemical monitoring effectively predicts iron supplementation needs in athletes. Personalized nutrition strategies, guided by TGS, can optimize iron status and enhance performance in elite football players. This approach bridges a critical gap in sports science, offering a framework for precision nutrition in athletics.