ACTN3 Variants Beyond Performance: Metabolic and Inflammatory Implications.
11 affiliations
- 1Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, 80131 Naples, Italy.
- 2CEINGE-Biotecnologie Avanzate, via Gaetano Salvatore 486, 80045 Naples, Italy.
- 3NutriSportHealthLab, University of Naples Federico II, Via Sergio Pansini 5, 80131 Naples, Italy.
- 4Division of Cardiology, University of Colorado School of Medicine, 12505 E. 16th Avenue, Anschutz Inpatient Pavilion 2, Aurora, CO 80045, USA.
- 5Department of Education and Sports Sciences, Pegaso Telematic University, 80143 Naples, Italy.
- 6SS Napoli Basket SRL, 80127 Naples, Italy.
- 7Centro Universitario Sportivo di Napoli, Via Campegna 267, 80124 Naples, Italy.
- 8Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, University of Campania "Luigi Vanvitelli", Via Vivaldi 43, 81100 Caserta, Italy.
- 9Department of Translational Medical Sciences, University of Naples "Federico II", 80131 Naples, Italy.
- 10Department of Medical, Human Movement and Well-Being Sciences, University Parthenope, Via Medina 40, 80133 Naples, Italy.
- 11Department of Medical, Oral and Biotechnological Sciences, Laboratory of Biostatistics, University G. d'Annunzio of Chieti-Pescara, 66100 Chieti, Italy.
Abstract
Background: Athletic performance is a result of interaction between genetic and environmental factors, including training, nutrition, rest, hormonal and psychophysiological status. Numerous genes and polymorphisms can influence key physiological processes, such as muscle contractility, energy metabolism, oxidative capacity, and cardiovascular efficiency. Among these, the ACTN3 gene, and in particular the polymorphism rs1815739 (NM_001104.4:c.1729C>T; p.Arg577Ter), is well known for its association with athletic performance, but emerging evidence suggests broader effects on metabolic and inflammatory phenotypes. Methods: For this study, 109 elite athletes were enrolled and genotyped for ACTN3 c.1729C>T by Sanger sequencing. Moreover, biochemical markers, such as creatine kinase (CK), C-reactive protein (CRP), lipid profile, adiponectin, and neutrophil-to-lymphocyte ratio (NLR), were examined. Finally, to better investigate the association between genotype and athletic performance, the genotypes and the results of standardized physical tests were correlated in a small exploratory subgroup of 28 professional basketball athletes. Normality was assessed using the Shapiro-Wilk test; non-normally distributed variables were summarized as median [IQR] and analyzed with non-parametric methods. Genotype comparisons were adjusted for multiple testing using the Holm procedure, and principal biochemical models were adjusted for age, BMI, sex, and ancestry. Results: The c.1729C>T genotype distribution differed between the two ancestry groups (exact p = 0.049), and all three variants were compatible with Hardy-Weinberg equilibrium within the ancestry groups. No biochemical genotype association remained statistically significant after Holm correction. In the performance subgroup, no genotype-performance association remained significant after Holm correction. Conclusions: In this cohort, the corrected analyses did not provide robust evidence for genotype-dependent biochemical or performance effects. The results are exploratory and require replication in larger cohorts, considering ancestry and gender differences.
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BibTeX
@article{imperatore2026actn3,
title = {{ACTN3 Variants Beyond Performance: Metabolic and Inflammatory Implications.}},
author = {Antonio Imperatore and Fernanda Iafusco and Mariella Calvanese and Alessandro Gentile and Raffaele Amitrano and Fabiana Di Fusco and Marta Mallardo and Gaetano Iaquinto and Mattia Digno and Salvatore Tamburro and Ersilia Nigro and Roberto Berni Canani and Annamaria Mancini and Pasqualina Buono and Cristina Mazzaccara and Barbara Lombardo and Daniela Terracciano and Giulia Frisso and Aurora Daniele and Paola Borrelli and Cristina Mennitti and Nadia Tinto and Olga Scudiero},
journal = {Genes},
year = {2026},
month = oct,
doi = {10.3390/genes17101280},
url = {https://europepmc.org/article/MED/42938396},
note = {CC BY},
}
RIS
TY - JOUR
TI - ACTN3 Variants Beyond Performance: Metabolic and Inflammatory Implications.
AU - Antonio Imperatore
AU - Fernanda Iafusco
AU - Mariella Calvanese
AU - Alessandro Gentile
AU - Raffaele Amitrano
AU - Fabiana Di Fusco
AU - Marta Mallardo
AU - Gaetano Iaquinto
AU - Mattia Digno
AU - Salvatore Tamburro
AU - Ersilia Nigro
AU - Roberto Berni Canani
AU - Annamaria Mancini
AU - Pasqualina Buono
AU - Cristina Mazzaccara
AU - Barbara Lombardo
AU - Daniela Terracciano
AU - Giulia Frisso
AU - Aurora Daniele
AU - Paola Borrelli
AU - Cristina Mennitti
AU - Nadia Tinto
AU - Olga Scudiero
PY - 2026
DA - 2026/10/14
JO - Genes
DO - 10.3390/genes17101280
UR - https://europepmc.org/article/MED/42938396
AB - Background: Athletic performance is a result of interaction between genetic and environmental factors, including training, nutrition, rest, hormonal and psychophysiological status. Numerous genes and polymorphisms can influence key physiological processes, such as muscle contractility, energy metabolism, oxidative capacity, and cardiovascular efficiency. Among these, the ACTN3 gene, and in particular the polymorphism rs1815739 (NM_001104.4:c.1729C>T; p.Arg577Ter), is well known for its association with athletic performance, but emerging evidence suggests broader effects on metabolic and inflammatory phenotypes. Methods: For this study, 109 elite athletes were enrolled and genotyped for ACTN3 c.1729C>T by Sanger sequencing. Moreover, biochemical markers, such as creatine kinase (CK), C-reactive protein (CRP), lipid profile, adiponectin, and neutrophil-to-lymphocyte ratio (NLR), were examined. Finally, to better investigate the association between genotype and athletic performance, the genotypes and the results of standardized physical tests were correlated in a small exploratory subgroup of 28 professional basketball athletes. Normality was assessed using the Shapiro-Wilk test; non-normally distributed variables were summarized as median [IQR] and analyzed with non-parametric methods. Genotype comparisons were adjusted for multiple testing using the Holm procedure, and principal biochemical models were adjusted for age, BMI, sex, and ancestry. Results: The c.1729C>T genotype distribution differed between the two ancestry groups (exact p = 0.049), and all three variants were compatible with Hardy-Weinberg equilibrium within the ancestry groups. No biochemical genotype association remained statistically significant after Holm correction. In the performance subgroup, no genotype-performance association remained significant after Holm correction. Conclusions: In this cohort, the corrected analyses did not provide robust evidence for genotype-dependent biochemical or performance effects. The results are exploratory and require replication in larger cohorts, considering ancestry and gender differences.
SN - 2073-4425
ER -