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 ACE (rs4646994), ACTN3 (rs1815739), AMPD1 (rs17602729), CKM (rs8111989), HFE (rs1799945), and MLCK (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 (ACE DD, ACTN3 CC, AMPD1 CC, HFE GC) required less iron supplementation (TGS = 51.25 vs. 41.32 a.u.; p = 0.013) and exhibited better performance metrics. Iron supplementation significantly improved haemoglobin and haematocrit in deficient players (p < 0.05). The TGS predicted supplementation need (AUC = 0.711; p = 0.023), with a threshold of 46.42 a.u. (OR = 5.23, 95% CI: 1.336-14.362; p = 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; p = 0.003), total distance covered (128,129.42 vs. 218,556.64 m; p = 0.005), and high-speed running in the 18-21 km/h (7.58 vs. 10.36 m/min; p = 0.007) and 21-24 km/h (4.43 vs. 6.13 m/min; p = 0.010) speed zones. They also started fewer matches (11.50 vs. 21.59; p < 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.

Keywords: football; genetic profile; iron supplementation; performance; personalized nutrition.

背景： 铁缺乏在精英运动员中是一个普遍问题，特别是在像足球这样的耐力运动项目中，其中最佳的铁状态对于有氧能力和表现至关重要。尽管已经充分记录了铁在氧气运输和能量代谢中的作用，但基因多态性、生化标志物与铁补充之间的相互关系仍然不甚了解。本研究旨在调查专业足球运动员中铁基因多态性和铁状态的关系，评估铁补充对运动表现的影响，并基于遗传和生化特征开发一个预测铁补充的模型。

方法： 一项历时三个赛季（2021-2024）的研究在48名男性专业足球运动员中进行。参与者进行了ACE (rs4646994)、ACTN3 (rs1815739)、AMPD1 (rs17602729)、CKM (rs8111989)、HFE (rs1799945) 和MLCK (rs2700352, rs28497577) 多态性的基因分型。监测了生化标志物（铁蛋白、血红蛋白、血细胞比容和血清铁）以及运动表现指标（GPS衍生数据）。对铁蛋白

结果： 具有“最佳”基因型(ACE DD, ACTN3 CC, AMPD1 CC, HFE GC) 的运动员需要的铁补充较少（TGS = 51.25 vs. 41.32 a.u.; p = 0.013），并且表现指标更好。对于缺铁球员，铁补充显著改善了血红蛋白和血细胞比容(p

结论： 结合遗传特征和生化监测能够有效预测运动员的铁补充需求。通过TGS指导个性化营养策略可以优化铁状态并提升精英足球运动员的表现。这种方法填补了体育科学中的一个重要空白，为运动领域的精准营养提供了框架。

关键词： 足球；基因特征；铁补充；表现；个性化营养。