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Background <p><i>ACTN3</i>, which encodes alpha-actinin-3 protein influences sports performance. A common genetic variation in the <i>ACTN3</i>, known as R577X, results in either a functional (R allele) or non-functional (X allele) protein, which alters the capabilities of a sportsperson. However, research on <i>ACTN3</i> genotype distribution and its association with physical performance in the South-Indian population remains limited.</p> Methodology <p>Genotyping of the <i>ACTN3</i> R577X polymorphism was performed in both sportspersons (SP) (N = 13) and non-sportspersons (NSP) (N = 26) using PCR–RFLP and confirmed by sequencing. Various physical performance, group comparison and its association with genotype was evaluated using standardized statistical tests. A p-value of &lt; 0.05 was considered significant.</p> Results <p>The XX-genotype frequency was observed in 69% of SP and 85% of NSP, while RX was present in 23% and 15% of SP and NSP respectively. SP demonstrated significantly higher performance than NSP in endurance and agility measures (p &lt; 0.05). Within the SP group, though the descriptive trend showed higher mean scores in endurance-related tests in individuals carrying the XX-genotype, no significant genotype-based differences were observed upon multivariate analysis.</p> Conclusion <p>While descriptive trends were observed among XX-carriers in certain endurance-related tasks, <i>ACTN3</i> genotype was not an independent predictor of performance after adjusting for training status. Furthermore, the similar genotype distribution between SP and NSP suggests that <i>ACTN3</i> variation alone does not determine athletic performance, underscoring the multifactorial nature of athletic ability. Larger, adequately powered studies integrating genetic, environmental, and training-related factors are required to better understand gene–environment interactions and their potential implications for personalized performance optimization.</p>

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The X genotype of the ACTN3 sports gene is associated with the endurance of the sportsperson from the South Indian population: a short study

  • 期刊论文

  • 发表日期：

    2026年4月10日

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  • K. M. Veena,
  • V. Mohammed Hasil,
  • Mohammad Amjad Hussain,
  • Suparna Laha,
  • Ranajit Das,
  • Prashanth Shenoy,
  • Laxmikanth Chatra,
  • Rachana Prabhu,
  • Prathima Shetty

摘要

Background

ACTN3, which encodes alpha-actinin-3 protein influences sports performance. A common genetic variation in the ACTN3, known as R577X, results in either a functional (R allele) or non-functional (X allele) protein, which alters the capabilities of a sportsperson. However, research on ACTN3 genotype distribution and its association with physical performance in the South-Indian population remains limited.

Methodology

Genotyping of the ACTN3 R577X polymorphism was performed in both sportspersons (SP) (N = 13) and non-sportspersons (NSP) (N = 26) using PCR–RFLP and confirmed by sequencing. Various physical performance, group comparison and its association with genotype was evaluated using standardized statistical tests. A p-value of < 0.05 was considered significant.

Results

The XX-genotype frequency was observed in 69% of SP and 85% of NSP, while RX was present in 23% and 15% of SP and NSP respectively. SP demonstrated significantly higher performance than NSP in endurance and agility measures (p < 0.05). Within the SP group, though the descriptive trend showed higher mean scores in endurance-related tests in individuals carrying the XX-genotype, no significant genotype-based differences were observed upon multivariate analysis.

Conclusion

While descriptive trends were observed among XX-carriers in certain endurance-related tasks, ACTN3 genotype was not an independent predictor of performance after adjusting for training status. Furthermore, the similar genotype distribution between SP and NSP suggests that ACTN3 variation alone does not determine athletic performance, underscoring the multifactorial nature of athletic ability. Larger, adequately powered studies integrating genetic, environmental, and training-related factors are required to better understand gene–environment interactions and their potential implications for personalized performance optimization.