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Konopka MJ, Keizer H, Rietjens G, Zeegers MP, Sperlich B. A critical examination of sport discipline typology: identifying inherent limitations and deficiencies in contemporary classification systems. Front Physiol 2024; 15:1389844. [PMID: 39050482 PMCID: PMC11266029 DOI: 10.3389/fphys.2024.1389844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 06/18/2024] [Indexed: 07/27/2024] Open
Abstract
Exercise scientists (especially in the field of biomolecular research) frequently classify athletic cohorts into categories such as endurance, strength, or mixed, and create a practical framework for studying diverse athletic populations between seemingly similar groups. It is crucial to recognize the limitations and complexities of these classifications, as they may oversimplify the multidimensional characteristics of each sport. If so, the validity of studies dealing with such approaches may become compromised and the comparability across different studies challenging or impossible. This perspective critically examines and highlights the issues associated with current sports typologies, critiques existing sports classification systems, and emphasizes the imperative for a universally accepted classification model to enhance the quality of biomolecular research of sports in the future.
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Affiliation(s)
- Magdalena Johanna Konopka
- Department of Epidemiology, Maastricht University, Maastricht, Netherlands
- Institute for Healthcare Management and Health Sciences, University of Bayreuth, Bayreuth, Germany
| | - Hans Keizer
- Department of Epidemiology, Maastricht University, Maastricht, Netherlands
| | - Gerard Rietjens
- Human Physiology and Sports Physiotherapy Research Group, Vrije Universiteit Brussel, Brussels, Belgium
| | - Maurice Petrus Zeegers
- Department of Epidemiology, Maastricht University, Maastricht, Netherlands
- MPB Holding, Heerlen, Netherlands
| | - Billy Sperlich
- Integrative and Experimental Exercise Science and Training, Institute of Sport Science, University of Würzburg, Würzburg, Germany
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Rostamzadeh S, Abouhossein A, Alam K, Vosoughi S, Sattari SS. Exploratory analysis using machine learning algorithms to predict pinch strength by anthropometric and socio-demographic features. INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS 2024; 30:518-531. [PMID: 38553890 DOI: 10.1080/10803548.2024.2322888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Objectives. This study examines the role of different machine learning (ML) algorithms to determine which socio-demographic factors and hand-forearm anthropometric dimensions can be used to accurately predict hand function. Methods. The cross-sectional study was conducted with 7119 healthy Iranian participants (3525 males and 3594 females) aged 10-89 years. Seventeen hand-forearm anthropometric dimensions were measured by JEGS digital caliper and a measuring tape. Tip-to-tip, key and three-jaw chuck pinches were measured using a calibrated pinch gauge. Subsequently, 21 features pertinent to socio-demographic factors and hand-forearm anthropometric dimensions were used for classification. Furthermore, 12 well-known classifiers were implemented and evaluated to predict pinches. Results. Among the 21 features considered in this study, hand length, stature, age, thumb length and index finger length were found to be the most relevant and effective components for each of the three pinch predictions. The k-nearest neighbor, adaptive boosting (AdaBoost) and random forest classifiers achieved the highest classification accuracy of 96.75, 86.49 and 84.66% to predict three pinches, respectively. Conclusions. Predicting pinch strength and determining the predictive hand-forearm anthropometric and socio-demographic characteristics using ML may pave the way to designing an enhanced tool handle and reduce common musculoskeletal disorders of the hand.
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Affiliation(s)
- Sajjad Rostamzadeh
- Department of Ergonomics, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Alireza Abouhossein
- Department of Ergonomics, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Khurshid Alam
- Department of Mechanical and Industrial Engineering, College of Engineering, Sultan Qaboos University, Muscat, Oman
| | - Shahram Vosoughi
- Department of Occupational Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
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Ahmetov II, John G, Semenova EA, Hall ECR. Genomic predictors of physical activity and athletic performance. ADVANCES IN GENETICS 2024; 111:311-408. [PMID: 38908902 DOI: 10.1016/bs.adgen.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/24/2024]
Abstract
Physical activity and athletic performance are complex phenotypes influenced by environmental and genetic factors. Recent advances in lifestyle and behavioral genomics led to the discovery of dozens of DNA polymorphisms (variants) associated with physical activity and allowed to use them as genetic instruments in Mendelian randomization studies for identifying the causal links between physical activity and health outcomes. On the other hand, exercise and sports genomics studies are focused on the search for genetic variants associated with athlete status, sports injuries and individual responses to training and supplement use. In this review, the findings of studies investigating genetic markers and their associations with physical activity and athlete status are reported. As of the end of September 2023, a total of 149 variants have been associated with various physical activity traits (of which 42 variants are genome-wide significant) and 253 variants have been linked to athlete status (115 endurance-related, 96 power-related, and 42 strength-related).
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Affiliation(s)
- Ildus I Ahmetov
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom; Sports Genetics Laboratory, St Petersburg Research Institute of Physical Culture, St. Petersburg, Russia; Laboratory of Genetics of Aging and Longevity, Kazan State Medical University, Kazan, Russia; Department of Physical Education, Plekhanov Russian University of Economics, Moscow, Russia.
| | - George John
- Transform Specialist Medical Centre, Dubai, United Arab Emirates
| | - Ekaterina A Semenova
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia; Research Institute of Physical Culture and Sport, Volga Region State University of Physical Culture, Sport and Tourism, Kazan, Russia
| | - Elliott C R Hall
- Faculty of Health Sciences and Sport, University of Stirling, Stirling, United Kingdom
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Semenova EA, Hall ECR, Ahmetov II. Genes and Athletic Performance: The 2023 Update. Genes (Basel) 2023; 14:1235. [PMID: 37372415 DOI: 10.3390/genes14061235] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 06/05/2023] [Accepted: 06/07/2023] [Indexed: 06/29/2023] Open
Abstract
Phenotypes of athletic performance and exercise capacity are complex traits influenced by both genetic and environmental factors. This update on the panel of genetic markers (DNA polymorphisms) associated with athlete status summarises recent advances in sports genomics research, including findings from candidate gene and genome-wide association (GWAS) studies, meta-analyses, and findings involving larger-scale initiatives such as the UK Biobank. As of the end of May 2023, a total of 251 DNA polymorphisms have been associated with athlete status, of which 128 genetic markers were positively associated with athlete status in at least two studies (41 endurance-related, 45 power-related, and 42 strength-related). The most promising genetic markers include the AMPD1 rs17602729 C, CDKN1A rs236448 A, HFE rs1799945 G, MYBPC3 rs1052373 G, NFIA-AS2 rs1572312 C, PPARA rs4253778 G, and PPARGC1A rs8192678 G alleles for endurance; ACTN3 rs1815739 C, AMPD1 rs17602729 C, CDKN1A rs236448 C, CPNE5 rs3213537 G, GALNTL6 rs558129 T, IGF2 rs680 G, IGSF3 rs699785 A, NOS3 rs2070744 T, and TRHR rs7832552 T alleles for power; and ACTN3 rs1815739 C, AR ≥21 CAG repeats, LRPPRC rs10186876 A, MMS22L rs9320823 T, PHACTR1 rs6905419 C, and PPARG rs1801282 G alleles for strength. It should be appreciated, however, that elite performance still cannot be predicted well using only genetic testing.
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Affiliation(s)
- Ekaterina A Semenova
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia
- Research Institute of Physical Culture and Sport, Volga Region State University of Physical Culture, Sport and Tourism, 420138 Kazan, Russia
| | - Elliott C R Hall
- Faculty of Health Sciences and Sport, University of Stirling, Stirling FK9 4UA, UK
| | - Ildus I Ahmetov
- Laboratory of Genetics of Aging and Longevity, Kazan State Medical University, 420012 Kazan, Russia
- Sports Genetics Laboratory, St Petersburg Research Institute of Physical Culture, 191040 St. Petersburg, Russia
- Department of Physical Education, Plekhanov Russian University of Economics, 115093 Moscow, Russia
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L3 5AF, UK
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Hsu CY, Sheu WHH, Lee IT. Brain-derived neurotrophic factor associated with kidney function. Diabetol Metab Syndr 2023; 15:16. [PMID: 36782254 PMCID: PMC9926783 DOI: 10.1186/s13098-023-00991-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 02/06/2023] [Indexed: 02/15/2023] Open
Abstract
BACKGROUND We examined the relationship between brain-derived neurotrophic factor (BDNF) and chronic kidney disease (CKD). METHODS First, a cross-sectional study was conducted in 480 participants without known diabetes. An oral glucose tolerance test (OGTT) was administered after overnight fasting, and blood samples were collected at 0, 30, and 120 min. Second, a total of 3003 participants were enrolled for the case-control genetic analysis. After assigning them to a case or a control group based on age and CKD status, we investigated the association between BDNF gene variants and susceptibility to CKD. RESULTS A higher fasting serum BDNF quartile was significantly associated with a lower prevalence of CKD (P value for trend < 0.001). Based on the receiver operating characteristic analysis, the fasting BDNF level had a larger area under the curve for differentiating CKD (0.645, 95% CI 0.583‒0.707) than the BDNF levels at both 30 min (0.547, 95% CI 0.481‒0.612) and 120 min (0.598, 95% CI 0.536‒0.661). A significantly lower CKD prevalence (odds ratio = 0.30, 95% CI 0.12‒0.71) was observed in the highest quartile of fasting BDNF level than that in the lowest quartile, whereas no interquartile differences were observed for BDNF levels determined at 30 or 120 min during the OGTT. Furthermore, BDNF-associated variants, including rs12098908, rs12577517, and rs72891405, were significantly associated with CKD. CONCLUSIONS The BDNF level at fasting, but not at 30 and 120 min after glucose intake, was an independent indicator of CKD. In addition, significant associations were observed between three BDNF gene variants and CKD.
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Affiliation(s)
- Cheng-Yueh Hsu
- Medical Education Department, Linkou Chang Gung Memorial Hospital, Taoyuan City, 33305, Taiwan
| | - Wayne Huey-Herng Sheu
- Department of Internal Medicine, Taipei Veterans General Hospital, Taipei, 11221, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan
| | - I-Te Lee
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan.
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, No. 1650 Taiwan Boulevard, Sect. 4, Taichung, 40705, Taiwan.
- School of Medicine, Chung Shan Medical University, Taichung, 40201, Taiwan.
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Identification and Characterization of Genomic Predictors of Sarcopenia and Sarcopenic Obesity Using UK Biobank Data. Nutrients 2023; 15:nu15030758. [PMID: 36771461 PMCID: PMC9920138 DOI: 10.3390/nu15030758] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/28/2023] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
The substantial decline in skeletal muscle mass, strength, and gait speed is a sign of severe sarcopenia, which may partly depend on genetic risk factors. So far, hundreds of genome-wide significant single nucleotide polymorphisms (SNPs) associated with handgrip strength, lean mass and walking pace have been identified in the UK Biobank cohort; however, their pleiotropic effects on all three phenotypes have not been investigated. By combining summary statistics of genome-wide association studies (GWAS) of handgrip strength, lean mass and walking pace, we have identified 78 independent SNPs (from 73 loci) associated with all three traits with consistent effect directions. Of the 78 SNPs, 55 polymorphisms were also associated with body fat percentage and 25 polymorphisms with type 2 diabetes (T2D), indicating that sarcopenia, obesity and T2D share many common risk alleles. Follow-up bioinformatic analysis revealed that sarcopenia risk alleles were associated with tiredness, falls in the last year, neuroticism, alcohol intake frequency, smoking, time spent watching television, higher salt, white bread, and processed meat intake; whereas protective alleles were positively associated with bone mineral density, serum testosterone, IGF1, and 25-hydroxyvitamin D levels, height, intelligence, cognitive performance, educational attainment, income, physical activity, ground coffee drinking and healthier diet (muesli, cereal, wholemeal or wholegrain bread, potassium, magnesium, cheese, oily fish, protein, water, fruit, and vegetable intake). Furthermore, the literature data suggest that single-bout resistance exercise may induce significant changes in the expression of 26 of the 73 implicated genes in m. vastus lateralis, which may partly explain beneficial effects of strength training in the prevention and treatment of sarcopenia. In conclusion, we have identified and characterized 78 SNPs associated with sarcopenia and 55 SNPs with sarcopenic obesity in European-ancestry individuals from the UK Biobank.
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Liang J, Zhang H, Zeng Z, Lv J, Huang J, Wu X, Wang M, Xu J, Fan J, Chen N. MicroRNA profiling of different exercise interventions for alleviating skeletal muscle atrophy in naturally aging rats. J Cachexia Sarcopenia Muscle 2023; 14:356-368. [PMID: 36457259 PMCID: PMC9891923 DOI: 10.1002/jcsm.13137] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/06/2022] [Accepted: 11/03/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Exercise is an affordable and practical strategy to alleviate several detrimental outcomes from the aging process, including sarcopenia. The elucidation of molecular mechanisms to alleviate sarcopenia is one of the most important steps towards understanding human aging. Although microRNAs (miRNAs) regulate muscle growth, regeneration and aging, the potential role of exercise-mediated miRNAs during the prevention and rehabilitation of skeletal muscle atrophy upon exercise interventions remains unclear. METHODS A miRNA profile by miRNA sequencing for gastrocnemius muscle of a 24-month-old aged male rat model mimicking the naturally aging process was established through screening the differentially expressed miRNAs (DEMs) for alleviating aging-induced skeletal muscle atrophy upon optimal exercise intervention. The screened miRNAs and hub genes, as well as biomarkers with the most significantly enriched pathways, were validated by quantitative real-time polymerase chain reaction and western blotting. RESULTS The sarcopenia index (SI) value and cross-sectional area (CSA) of rats from the old control (OC) group significantly decreased when compared with the youth control (YC) group (P < 0.001, P < 0.01), whereas an increased SI value and an enlarged CSA of rats from the old-aerobic exercise (OE), old-resistance exercise (OR) and old-mixed exercise (OM) groups were determined (P < 0.01, P < 0.001, P < 0.05; P < 0.01, P < 0.01, P < 0.05). Our results demonstrate that 764 known miRNAs, 201 novel miRNAs and 505 miRNA-mRNA interaction networks were identified to be related to aging-induced muscular atrophy. Among them, 13 miRNAs were differentially expressed (P < 0.05 and log2 |fold change| > 1) between the YC group and the OC group. Compared with the OC group, 7, 2 and 11 miRNAs were differentially expressed in the OE, OR and OM groups after exercise interventions, respectively. Meanwhile, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the identified DEMs were primarily related to apoptosis, autophagy and the NF-κB/MuRF1 signalling pathways (P < 0.05). Meanwhile, four DEMs (miR-7a-1-3p, miR-135a-5p, miR-151-5p and miR-196b-5p), six hub genes (Ar, Igf1, Hif1a, Bdnf, Fak and Nras) and several biomarkers (LC3, Beclin1, p62, Bax, Bcl-2 and NF-κB/MuRF1) with the most significantly enriched pathways were confirmed, which may play a key role in muscular atrophy during the aging process. CONCLUSIONS These findings are closely correlated with the progression of sarcopenia and could act as potential biomarkers for the diagnosis and interventional monitoring of aging-induced skeletal muscle atrophy.
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Affiliation(s)
- Jiling Liang
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
| | - Hu Zhang
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
| | - Zhengzhong Zeng
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
| | - Jun Lv
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
| | - Jielun Huang
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
| | - Xiaowen Wu
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
| | - Minghui Wang
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
| | - Jiahao Xu
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
| | - Jingjing Fan
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
| | - Ning Chen
- Tianjiu Research and Development Center for Exercise Nutrition and Foods, Hubei Key Laboratory of Exercise Training and Monitoring, College of Health Science, Wuhan Sports University, Wuhan, Hubei, China
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Semenova EA, Zempo H, Miyamoto-Mikami E, Kumagai H, Larin AK, Sultanov RI, Babalyan KA, Zhelankin AV, Tobina T, Shiose K, Kakigi R, Tsuzuki T, Ichinoseki-Sekine N, Kobayashi H, Naito H, Burniston J, Generozov EV, Fuku N, Ahmetov II. Genome-Wide Association Study Identifies CDKN1A as a Novel Locus Associated with Muscle Fiber Composition. Cells 2022; 11:cells11233910. [PMID: 36497168 PMCID: PMC9737696 DOI: 10.3390/cells11233910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 11/24/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
Muscle fiber composition is associated with physical performance, with endurance athletes having a high proportion of slow-twitch muscle fibers compared to power athletes. Approximately 45% of muscle fiber composition is heritable, however, single nucleotide polymorphisms (SNP) underlying inter-individual differences in muscle fiber types remain largely unknown. Based on three whole genome SNP datasets, we have shown that the rs236448 A allele located near the cyclin-dependent kinase inhibitor 1A (CDKN1A) gene was associated with an increased proportion of slow-twitch muscle fibers in Russian (n = 151; p = 0.039), Finnish (n = 287; p = 0.03), and Japanese (n = 207; p = 0.008) cohorts (meta-analysis: p = 7.9 × 10−5. Furthermore, the frequency of the rs236448 A allele was significantly higher in Russian (p = 0.045) and Japanese (p = 0.038) elite endurance athletes compared to ethnically matched power athletes. On the contrary, the C allele was associated with a greater proportion of fast-twitch muscle fibers and a predisposition to power sports. CDKN1A participates in cell cycle regulation and is suppressed by the miR-208b, which has a prominent role in the activation of the slow myofiber gene program. Bioinformatic analysis revealed that the rs236448 C allele was associated with increased CDKN1A expression in whole blood (p = 8.5 × 10−15) and with greater appendicular lean mass (p = 1.2 × 10−5), whereas the A allele was associated with longer durations of exercise (p = 0.044) reported amongst the UK Biobank cohort. Furthermore, the expression of CDKN1A increased in response to strength (p < 0.0001) or sprint (p = 0.00035) training. Accordingly, we found that CDKN1A expression is significantly (p = 0.002) higher in the m. vastus lateralis of strength athletes compared to endurance athletes and is positively correlated with the percentage of fast-twitch muscle fibers (p = 0.018). In conclusion, our data suggest that the CDKN1A rs236448 SNP may be implicated in the determination of muscle fiber composition and may affect athletic performance.
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Affiliation(s)
- Ekaterina A. Semenova
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia
- Research Institute of Physical Culture and Sport, Volga Region State University of Physical Culture, Sport and Tourism, 420138 Kazan, Russia
| | - Hirofumi Zempo
- Faculty of Health and Nutrition, Tokyo Seiei College, Tokyo 124-0025, Japan
| | - Eri Miyamoto-Mikami
- Graduate School of Health and Sports Science, Juntendo University, Chiba 270-1695, Japan
| | - Hiroshi Kumagai
- Graduate School of Health and Sports Science, Juntendo University, Chiba 270-1695, Japan
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Andrey K. Larin
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia
| | - Rinat I. Sultanov
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia
| | - Konstantin A. Babalyan
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia
| | - Andrey V. Zhelankin
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia
| | - Takuro Tobina
- Faculty of Nursing and Nutrition, University of Nagasaki, Nagasaki 851-2195, Japan
| | - Keisuke Shiose
- Faculty of Education, University of Miyazaki, Miyazaki 889-2192, Japan
| | - Ryo Kakigi
- Faculty of Management & Information Science, Josai International University, Chiba 283-8555, Japan
| | | | - Noriko Ichinoseki-Sekine
- Graduate School of Health and Sports Science, Juntendo University, Chiba 270-1695, Japan
- Faculty of Liberal Arts, The Open University of Japan, Chiba 261-8586, Japan
| | - Hiroyuki Kobayashi
- Department of General Medicine, Mito Medical Center, Tsukuba University Hospital, Ibaraki 310-0015, Japan
| | - Hisashi Naito
- Graduate School of Health and Sports Science, Juntendo University, Chiba 270-1695, Japan
| | - Jatin Burniston
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L3 5AF, UK
| | - Edward V. Generozov
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia
| | - Noriyuki Fuku
- Graduate School of Health and Sports Science, Juntendo University, Chiba 270-1695, Japan
| | - Ildus I. Ahmetov
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L3 5AF, UK
- Department of Physical Education, Plekhanov Russian University of Economics, 115093 Moscow, Russia
- Laboratory of Genetics of Aging and Longevity, Kazan State Medical University, 420012 Kazan, Russia
- Correspondence:
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Brain-derived neurotrophic factor (BDNF): a multifaceted marker in chronic kidney disease. Clin Exp Nephrol 2022; 26:1149-1159. [DOI: 10.1007/s10157-022-02268-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 08/18/2022] [Indexed: 11/03/2022]
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Abstract
Sports genomics is the scientific discipline that focuses on the organization and function of the genome in elite athletes, and aims to develop molecular methods for talent identification, personalized exercise training, nutritional need and prevention of exercise-related diseases. It postulates that both genetic and environmental factors play a key role in athletic performance and related phenotypes. This update on the panel of genetic markers (DNA polymorphisms) associated with athlete status and soft-tissue injuries covers advances in research reported in recent years, including one whole genome sequencing (WGS) and four genome-wide association (GWAS) studies, as well as findings from collaborative projects and meta-analyses. At end of 2020, the total number of DNA polymorphisms associated with athlete status was 220, of which 97 markers have been found significant in at least two studies (35 endurance-related, 24 power-related, and 38 strength-related). Furthermore, 29 genetic markers have been linked to soft-tissue injuries in at least two studies. The most promising genetic markers include HFE rs1799945, MYBPC3 rs1052373, NFIA-AS2 rs1572312, PPARA rs4253778, and PPARGC1A rs8192678 for endurance; ACTN3 rs1815739, AMPD1 rs17602729, CPNE5 rs3213537, CKM rs8111989, and NOS3 rs2070744 for power; LRPPRC rs10186876, MMS22L rs9320823, PHACTR1 rs6905419, and PPARG rs1801282 for strength; and COL1A1 rs1800012, COL5A1 rs12722, COL12A1 rs970547, MMP1 rs1799750, MMP3 rs679620, and TIMP2 rs4789932 for soft-tissue injuries. It should be appreciated, however, that hundreds and even thousands of DNA polymorphisms are needed for the prediction of athletic performance and injury risk.
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Ginevičienė V, Utkus A, Pranckevičienė E, Semenova EA, Hall ECR, Ahmetov II. Perspectives in Sports Genomics. Biomedicines 2022; 10:298. [PMID: 35203507 PMCID: PMC8869752 DOI: 10.3390/biomedicines10020298] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 01/24/2022] [Accepted: 01/25/2022] [Indexed: 12/04/2022] Open
Abstract
Human athletic performance is a complex phenotype influenced by environmental and genetic factors, with most exercise-related traits being polygenic in nature. The aim of this article is to outline some of the challenge faced by sports genetics as this relatively new field moves forward. This review summarizes recent advances in sports science and discusses the impact of the genome, epigenome and other omics (such as proteomics and metabolomics) on athletic performance. The article also highlights the current status of gene doping and examines the possibility of applying genetic knowledge to predict athletes' injury risk and to prevent the rare but alarming occurrence of sudden deaths during sporting events. Future research in large cohorts of athletes has the potential to detect new genetic variants and to confirm the previously identified DNA variants believed to explain the natural predisposition of some individuals to certain athletic abilities and health benefits. It is hoped that this article will be useful to sports scientists who seek a greater understanding of how genetics influences exercise science and how genomic and other multi-omics approaches might support performance analysis, coaching, personalizing nutrition, rehabilitation and sports medicine, as well as the potential to develop new rationale for future scientific investigation.
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Affiliation(s)
- Valentina Ginevičienė
- Institute of Biomedical Science, Faculty of Medicine, Vilnius University, 01513 Vilnius, Lithuania; (A.U.); (E.P.)
| | - Algirdas Utkus
- Institute of Biomedical Science, Faculty of Medicine, Vilnius University, 01513 Vilnius, Lithuania; (A.U.); (E.P.)
| | - Erinija Pranckevičienė
- Institute of Biomedical Science, Faculty of Medicine, Vilnius University, 01513 Vilnius, Lithuania; (A.U.); (E.P.)
- Department of Systems Analysis, Faculty of Informatics, Vytautas Magnus University, 44248 Kaunas, Lithuania
| | - Ekaterina A. Semenova
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia;
- Research Institute of Physical Culture and Sport, Volga Region State University of Physical Culture, Sport and Tourism, 420010 Kazan, Russia
| | - Elliott C. R. Hall
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L3 5AF, UK;
| | - Ildus I. Ahmetov
- Department of Molecular Biology and Genetics, Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, 119435 Moscow, Russia;
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool L3 5AF, UK;
- Department of Physical Education, Plekhanov Russian University of Economics, 115093 Moscow, Russia
- Laboratory of Molecular Genetics, Kazan State Medical University, 420012 Kazan, Russia
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Are Resistance Training-Induced BDNF in Hemodialysis Patients Associated with Depressive Symptoms, Quality of Life, Antioxidant Capacity, and Muscle Strength? An Insight for the Muscle-Brain-Renal Axis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182111299. [PMID: 34769814 PMCID: PMC8583357 DOI: 10.3390/ijerph182111299] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 10/22/2021] [Accepted: 10/24/2021] [Indexed: 12/28/2022]
Abstract
Background: Hemodialysis patients are suffering from depressive symptoms. Brain-derived neurotrophic factor (BDNF) levels are negatively associated with depressive symptoms and decrease during a single hemodialysis session. Resistance training (RT) might be an additional non-pharmacological tool to increase BDNF and promote mental health. Methods: Two randomized groups of hemodialysis patients: control (CTL, n = 76/F36; 66.33 ± 3.88 years) and RT (n = 81/F35; 67.27 ± 3.24 years). RT completed six months of training thrice a week under the supervision of strength and conditioning professional immediately before the dialysis session. Training loads were adjusted using the OMNI rating of perceived exertion. The total antioxidant capacity (TROLOX), glutathione (GSH), thiobarbituric acid reactive substance (TBARS), and BDNF levels were analyzed in serum samples. Quality of life (assessed through Medical Outcomes—SF36), and Beck Depression Inventory was applied. Results: RT improved handgrip strength (21.17 ± 4.38 vs. 27.17 ± 4.34; p = 0.001) but not for CTL (20.09 ± 5.19 vs. 19.75 ± 5.54; p = 0.001). Post-training, RT group had higher values as compared to CTL related to TROLOX (RT,680.8 ± 225.2 vs. CTL,589.5 ± 195.9; p = 0.001) and GSH (RT, 9.33 ± 2.09 vs. CTL,5.00 ± 2.96; p = 0.001). RT group had lower values of TBARS as compared to CTL at post-training (RT, 11.06 ± 2.95 vs. CTL, 13.66 ± 2.62; p = 0.001). BDNF increased for RT (11.66 ± 5.20 vs. 19.60 ± 7.23; p = 0.001), but decreased for CTL (14.40 ± 4.99 vs. 10.84 ± 5.94; p = 0.001). Quality of life and mental health increased (p = 0.001) for RT, but did not change for CTL (p = 0.001). BDNF levels were associated with emotional dimensions of SF36, depressive symptoms, and handgrip (p = 0.001). Conclusions: RT was effective as a non-pharmacological tool to increased BDNF levels, quality of life, temper the redox balance and decrease depressive symptoms intensity in hemodialysis patients.
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