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Pedroza Matute S, Turvey K, Iyavoo S. Advancing human genotyping: The Infinium HTS iSelect Custom microarray panel (Rita) development study. Forensic Sci Int Genet 2024; 71:103049. [PMID: 38653142 DOI: 10.1016/j.fsigen.2024.103049] [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] [Received: 12/15/2023] [Revised: 04/04/2024] [Accepted: 04/15/2024] [Indexed: 04/25/2024]
Abstract
Single Nucleotide Polymorphisms (SNPs), as the most prevalent type of variation in the human genome, play a pivotal role in influencing human traits. They are extensively utilized in diverse fields such as population genetics, forensic science, and genetic medicine. This study focuses on the 'Rita' BeadChip, a custom SNP microarray panel developed using Illumina Infinium HTS technology. Designed for high-throughput genotyping, the panel facilitates the analysis of over 4000 markers efficiently and cost-effectively. After careful clustering performed on a set of 1000 samples, an evaluation of the Rita panel was undertaken, assessing its sensitivity, repeatability, reproducibility, precision, accuracy, and resistance to contamination. The panel's performance was evaluated in various scenarios, including sex estimation and parental relationship assessment, using GenomeStudio data analysis software. Findings show that over 95 % of the custom BeadChip assay markers were successful, with better performance of transitions over other mutations, and a considerably lower success rate for Y chromosome loci. An exceptional call rate exceeding 99 % was demonstrated for control samples, even with DNA input as low as 0.781 ng. Call rates above 80 % were still obtained with DNA quantities under 0.1 ng, indicating high sensitivity and suitability for forensic applications where DNA quantity is often limited. Repeatability, reproducibility, and precision studies revealed consistency of the panel's performance across different batches and operators, with no significant deviations in call rates or genotyping results. Accuracy assessments, involving comparison with multiple available genetic databases, including the 1000 Genome Project and HapMap, denoted over 99 % concordance, establishing the Rita panel's reliability in genotyping. The contamination study revealed insights into background noise and allowed the definition of thresholds for sample quality evaluation. Multiple metrics for differentiating between negative controls and true samples were highlighted, increasing the reliability of the obtained results. The sex estimation tool in GenomeStudio proved highly effective, correctly assigning sex in all samples with autosomal loci call rates above 97 %. The parental relationship assessment of family trios highlighted the utility of GenomeStudio in identifying genotyping errors or potential Mendelian inconsistencies, promoting the application of arrays such as Rita in kinship testing. Overall, this evaluation confirms the Rita microarray as a robust, high-throughput genotyping tool, underscoring its potential in genetic research and forensic applications. With its custom content and adaptable design, it not only meets current genotyping demands but also opens avenues for further research and application expansion in the field of genetic analysis.
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Affiliation(s)
| | - Kiera Turvey
- IDna Genetics Limited, Scottow Enterprise Park, Norwich, Norfolk NR10 5FB, United Kingdom
| | - Sasitaran Iyavoo
- IDna Genetics Limited, Scottow Enterprise Park, Norwich, Norfolk NR10 5FB, United Kingdom; School of Chemistry, College of Health and Science, University of Lincoln, Lincoln, Lincolnshire LN6 7TS, United Kingdom.
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Konopka MJ, Sperlich B, Rietjens G, Zeegers MP. Genetics and athletic performance: a systematic SWOT analysis of non-systematic reviews. Front Genet 2023; 14:1232987. [PMID: 37621703 PMCID: PMC10445150 DOI: 10.3389/fgene.2023.1232987] [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: 06/08/2023] [Accepted: 07/26/2023] [Indexed: 08/26/2023] Open
Abstract
Exercise genetics/genomics is a growing research discipline comprising several Strengths and Opportunities but also deals with Weaknesses and Threats. This "systematic SWOT overview of non-systematic reviews" (sSWOT) aimed to identify the Strengths, Weaknesses, Opportunities, and Threats linked to exercise genetics/genomics. A systematic search was conducted in the Medline and Embase databases for non-systematic reviews to provide a comprehensive overview of the current literature/research area. The extracted data was thematically analyzed, coded, and categorized into SWOT clusters. In the 45 included reviews five Strengths, nine Weaknesses, six Opportunities, and three Threats were identified. The cluster of Strengths included "advances in technology", "empirical evidence", "growing research discipline", the "establishment of consortia", and the "acceptance/accessibility of genetic testing". The Weaknesses were linked to a "low research quality", the "complexity of exercise-related traits", "low generalizability", "high costs", "genotype scores", "reporting bias", "invasive methods", "research progress", and "causality". The Opportunities comprised of "precision exercise", "omics", "multicenter studies", as well as "genetic testing" as "commercial"-, "screening"-, and "anti-doping" detection tool. The Threats were related to "ethical issues", "direct-to-consumer genetic testing companies", and "gene doping". This overview of the present state of the art research in sport genetics/genomics indicates a field with great potential, while also drawing attention to the necessity for additional advancement in methodological and ethical guidance to mitigate the recognized Weaknesses and Threats. The recognized Strengths and Opportunities substantiate the capability of genetics/genomics to make significant contributions to the performance and wellbeing of athletes.
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Affiliation(s)
- Magdalena Johanna Konopka
- Care and Public Health Research Institute, Maastricht University, Maastricht, Netherlands
- Department of Epidemiology, Maastricht University, Maastricht, Netherlands
| | - Billy Sperlich
- Integrative and Experimental Exercise Science and Training, Institute of Sport Science, University of Würzburg, Würzburg, Germany
| | - Gerard Rietjens
- Human Physiology and Sports Physiotherapy Research Group, Vrije Universiteit Brussel, Brussels, Belgium
| | - Maurice Petrus Zeegers
- Care and Public Health Research Institute, Maastricht University, Maastricht, Netherlands
- Department of Epidemiology, Maastricht University, Maastricht, Netherlands
- School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, Netherlands
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3
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Khairul EE, Ab Wahab WA, Kek Teh L, Salleh MZ, Rofiee MS, Raja Azidin RMF, Md. Yusof S. The Predictive Ability of Total Genotype Score and Serum Metabolite Markers in Power-Based Sports Performance Following Different Strength Training Intensities — A Pilot Study. PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY 2023. [DOI: 10.47836/pjst.31.2.23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/20/2023]
Abstract
Muscular power is one of the factors that contribute to an athlete’s performance. This study aimed to explore the predictive ability of total genotype score (TGS) and serum metabolite markers in power-based sports performance following different strength training (ST) intensities. We recruited 15 novice male field hockey players (age = 16.27 ± .12 years old, body mass index = 22.57 ± 2.21 kg/m2) and allocated them to; high-intensity strength training (HIST, n=5), moderate intensity strength (MIST, n=5), and control group (C, n=5). Both training groups completed an eight-week ST intervention. Pre- and post-training muscular power (vertical jump) was measured. The participants were genotyped for; ACE (rs1799752), ACTN3 (rs1815739), ADRB3 (rs4994), AGT (rs699), BDKRB2 (rs1799722), PPARA (rs4253778), PPARGC1A (rs8192678), TRHR (rs7832552), and VEGF (rs1870377). TGS was calculated to annotate for strength-power (STP) and endurance (END) qualities. Subsequently, serum metabolomics analysis was conducted using Liquid chromatography-mass spectrometry Quadrupole-Time-of-Flight (LC-MS QTOF) to profile differentially expressed metabolite changes induced by training. Multiple regression analysis was conducted to explore the ability of TGS and differentially expressed metabolite markers to predict muscular power changes following the intervention. Multiple Regression revealed that only TGS STP might be a significant predictor of muscular power changes following MIST (adjusted R2=.906, p<.05). Additionally, ST also resulted in significant muscular power improvement (p<.05) and perturbation of the sphingolipid metabolism pathway (p<.05). Therefore, selected gene variants may influence muscular power. Therefore, STP TGS might be able to predict muscular power changes following MIST.
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4
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Venckunas T, Degens H. Genetic polymorphisms of muscular fitness in young healthy men. PLoS One 2022; 17:e0275179. [PMID: 36166425 PMCID: PMC9514622 DOI: 10.1371/journal.pone.0275179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 09/12/2022] [Indexed: 11/30/2022] Open
Abstract
The effects of genetic polymorphisms on muscle structure and function remain elusive. The present study tested for possible associations of 16 polymorphisms (across ten candidate genes) with fittness and skeletal muscle phenotypes in 17- to 37-year-old healthy Caucasian male endurance (n = 86), power/strength (n = 75) and team athletes (n = 60), and non-athletes (n = 218). Skeletal muscle function was measured with eight performance tests covering multiple aspects of muscular fitness. Along with body mass and height, the upper arm and limb girths, and maximal oxygen uptake were measured. Genotyping was conducted on DNA extracted from blood. Of the 16 polymorphisms studied, nine (spanning seven candidate genes and four gene families/signalling pathways) were independently associated with at least one skeletal muscle fitness measure (size or function, or both) measure and explained up to 4.1% of its variation. Five of the studied polymorphisms (activin- and adreno-receptors, as well as myosine light chain kinase 1) in a group of one to three combined with body height, age and/or group explained up to 20.4% of the variation of muscle function. ACVR1B (rs2854464) contributed 2.0–3.6% to explain up to 14.6% of limb proximal girths. The G allele (genotypes AG and GG) of the ACVR1B (rs2854464) polymorphism was significantly overrepresented among team (60.4%) and power (62.0%) athletes compared to controls (52.3%) and endurance athletes (39.2%), and G allele was also most consistently/frequently associated with muscle size and power. Overall, the investigated polymorphisms determined up to 4.1% of the variability of muscular fitness in healthy young humans.
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Affiliation(s)
- Tomas Venckunas
- Institute of Sport Science and Innovations, Lithuanian Sports University, Kaunas, Lithuania
- * E-mail:
| | - Hans Degens
- Institute of Sport Science and Innovations, Lithuanian Sports University, Kaunas, Lithuania
- Department of Life Sciences, Musculoskeletal Science and Sports Medicine Research Centre, Institute of Sport, Manchester Metropolitan University, Manchester, United Kingdom
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5
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Wang Z, Emmerich A, Pillon NJ, Moore T, Hemerich D, Cornelis MC, Mazzaferro E, Broos S, Ahluwalia TS, Bartz TM, Bentley AR, Bielak LF, Chong M, Chu AY, Berry D, Dorajoo R, Dueker ND, Kasbohm E, Feenstra B, Feitosa MF, Gieger C, Graff M, Hall LM, Haller T, Hartwig FP, Hillis DA, Huikari V, Heard-Costa N, Holzapfel C, Jackson AU, Johansson Å, Jørgensen AM, Kaakinen MA, Karlsson R, Kerr KF, Kim B, Koolhaas CM, Kutalik Z, Lagou V, Lind PA, Lorentzon M, Lyytikäinen LP, Mangino M, Metzendorf C, Monroe KR, Pacolet A, Pérusse L, Pool R, Richmond RC, Rivera NV, Robiou-du-Pont S, Schraut KE, Schulz CA, Stringham HM, Tanaka T, Teumer A, Turman C, van der Most PJ, Vanmunster M, van Rooij FJA, van Vliet-Ostaptchouk JV, Zhang X, Zhao JH, Zhao W, Balkhiyarova Z, Balslev-Harder MN, Baumeister SE, Beilby J, Blangero J, Boomsma DI, Brage S, Braund PS, Brody JA, Bruinenberg M, Ekelund U, Liu CT, Cole JW, Collins FS, Cupples LA, Esko T, Enroth S, Faul JD, Fernandez-Rhodes L, Fohner AE, Franco OH, Galesloot TE, Gordon SD, Grarup N, Hartman CA, Heiss G, Hui J, Illig T, Jago R, James A, Joshi PK, Jung T, Kähönen M, Kilpeläinen TO, Koh WP, Kolcic I, Kraft PP, Kuusisto J, Launer LJ, Li A, Linneberg A, Luan J, Vidal PM, Medland SE, Milaneschi Y, Moscati A, Musk B, Nelson CP, Nolte IM, Pedersen NL, Peters A, Peyser PA, Power C, Raitakari OT, Reedik M, Reiner AP, Ridker PM, Rudan I, Ryan K, Sarzynski MA, Scott LJ, Scott RA, Sidney S, Siggeirsdottir K, Smith AV, Smith JA, Sonestedt E, Strøm M, Tai ES, Teo KK, Thorand B, Tönjes A, Tremblay A, Uitterlinden AG, Vangipurapu J, van Schoor N, Völker U, Willemsen G, Williams K, Wong Q, Xu H, Young KL, Yuan JM, Zillikens MC, Zonderman AB, Ameur A, Bandinelli S, Bis JC, Boehnke M, Bouchard C, Chasman DI, Smith GD, de Geus EJC, Deldicque L, Dörr M, Evans MK, Ferrucci L, Fornage M, Fox C, Garland T, Gudnason V, Gyllensten U, Hansen T, Hayward C, Horta BL, Hyppönen E, Jarvelin MR, Johnson WC, Kardia SLR, Kiemeney LA, Laakso M, Langenberg C, Lehtimäki T, Marchand LL, Magnusson PKE, Martin NG, Melbye M, Metspalu A, Meyre D, North KE, Ohlsson C, Oldehinkel AJ, Orho-Melander M, Pare G, Park T, Pedersen O, Penninx BWJH, Pers TH, Polasek O, Prokopenko I, Rotimi CN, Samani NJ, Sim X, Snieder H, Sørensen TIA, Spector TD, Timpson NJ, van Dam RM, van der Velde N, van Duijn CM, Vollenweider P, Völzke H, Voortman T, Waeber G, Wareham NJ, Weir DR, Wichmann HE, Wilson JF, Hevener AL, Krook A, Zierath JR, Thomis MAI, Loos RJF, Hoed MD. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention. Nat Genet 2022; 54:1332-1344. [PMID: 36071172 PMCID: PMC9470530 DOI: 10.1038/s41588-022-01165-1] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 07/18/2022] [Indexed: 02/02/2023]
Abstract
Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.
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Affiliation(s)
- Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Andrew Emmerich
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Nicolas J Pillon
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Tim Moore
- Division of Cardiology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Daiane Hemerich
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marilyn C Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Eugenia Mazzaferro
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Siacia Broos
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Exercise Physiology Research Group, KU Leuven, Leuven, Belgium
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Physical Activity, Sports & Health Research Group, KU Leuven, Leuven, Belgium
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Mike Chong
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Audrey Y Chu
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- GlaxoSmithKline, Cambridge, MA, USA
| | - Diane Berry
- Division of Population, Policy and Practice, Great Ormond Street Hospital Institute for Child Health, University College London, London, UK
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Nicole D Dueker
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, USA
- Department of Epidemiology & Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Elisa Kasbohm
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- Institute of Mathematics and Computer Science, University of Greifswald, Greifswald, Germany
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Leanne M Hall
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Toomas Haller
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fernando P Hartwig
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
- MRC Integrative Epidemiology Unit, NIHR Bristol Biomedical Research Center, University of Bristol, Bristol, UK
| | - David A Hillis
- Genetics, Genomics, and Bioinformatics Graduate Program, University of California, Riverside, CA, USA
| | - Ville Huikari
- Institute of Health Sciences, University of Oulu, Oulu, Finland
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Christina Holzapfel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
- Institute for Nutritional Medicine, School of Medicine, Technical University of Munich, Munich, Germany
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Åsa Johansson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Anja Moltke Jørgensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marika A Kaakinen
- Section of Statistical Multi-omics, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kathleen F Kerr
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Boram Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea
| | - Chantal M Koolhaas
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Zoltan Kutalik
- University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | | | - Penelope A Lind
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Biomedical Science, Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Mattias Lorentzon
- Geriatric Medicine, Institute of Medicine, University of Gothenburg and Sahlgrenska University Hospital Mölndal, Gothenburg, Sweden
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Finnish Cardiovascular Research Center - Tampere, Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
- NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, UK
| | - Christoph Metzendorf
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden
| | - Kristine R Monroe
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Alexander Pacolet
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Exercise Physiology Research Group, KU Leuven, Leuven, Belgium
| | - Louis Pérusse
- Department of Kinesiology, Université Laval, Quebec, Quebec, Canada
- Centre Nutrition Santé et Société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, Quebec, Canada
| | - Rene Pool
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit and Avon Longitudinal Study of Parents and Children, University of Bristol Medical School, Population Health Sciences and Avon Longitudinal Study of Parents and Children, University of Bristol, Bristol, UK
| | - Natalia V Rivera
- Respiratory Division, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
- Rheumatology Division, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
- Center of Molecular Medicine (CMM), Karolinska Institutet, Stockholm, Sweden
| | - Sebastien Robiou-du-Pont
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Katharina E Schraut
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Christina-Alexandra Schulz
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Department of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Bonn, Germany
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
| | - Constance Turman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Mathias Vanmunster
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Exercise Physiology Research Group, KU Leuven, Leuven, Belgium
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Jana V van Vliet-Ostaptchouk
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Xiaoshuai Zhang
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- School of Public Health, Department of Biostatistics, Shandong University, Jinan, China
| | - Jing-Hua Zhao
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Zhanna Balkhiyarova
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Clinical and Experimental Medicine, University of Surrey, Guilford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guilford, UK
| | - Marie N Balslev-Harder
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sebastian E Baumeister
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- University of Münster, Münster, Germany
| | - John Beilby
- Diagnostic Genomics, PathWest Laboratory Medicine WA, Perth, Western Australia, Australia
| | - John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX, USA
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Soren Brage
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Peter S Braund
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - Ulf Ekelund
- Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway
- Department of Chronic Diseases, Norwegian Institute of Public Health, Oslo, Norway
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - John W Cole
- Vascular Neurology, Department of Neurology, University of Maryland School of Medicine and the Baltimore VAMC, Baltimore, MD, USA
| | - Francis S Collins
- Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - L Adrienne Cupples
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Tõnu Esko
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Stefan Enroth
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Lindsay Fernandez-Rhodes
- Department of Biobehavioral Health, College of Health and Human Development, Pennsylvania State University, University Park, PA, USA
| | - Alison E Fohner
- Department of Epidemiology, Institute of Public Health Genetics, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Oscar H Franco
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland
| | - Tessel E Galesloot
- Radboud Institute for Health Sciences, Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Scott D Gordon
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Catharina A Hartman
- Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Gerardo Heiss
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Jennie Hui
- Diagnostic Genomics, PathWest Laboratory Medicine WA, Perth, Western Australia, Australia
- School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia
- Busselton Population Medical Research Institute, Busselton, Western Australia, Australia
| | - Thomas Illig
- Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
- Department of Human Genetics, Hannover Medical School, Hannover, Germany
| | - Russell Jago
- Centre for Exercise Nutrition & Health Sciences, School for Policy Studies, University of Bristol, Bristol, UK
| | - Alan James
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Western Australia, Perth, Australia
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- Humanity Inc, Boston, MA, USA
| | - Taeyeong Jung
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea
| | - Mika Kähönen
- Finnish Cardiovascular Research Center - Tampere, Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Ivana Kolcic
- Department of Public Health, University of Split School of Medicine, Split, Croatia
| | - Peter P Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institutes of Health, Baltimore, MD, USA
| | - Aihua Li
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Allan Linneberg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Pedro Marques Vidal
- Division of Internal Medicine, Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Sarah E Medland
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- School of Psychology and Faculty of Medicine, University of Queensland, St Lucia, Queensland, Australia
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bill Musk
- Busselton Population Medical Research Institute, Busselton, Western Australia, Australia
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Christine Power
- Division of Population, Policy and Practice, Great Ormond Street Hospital Institute for Child Health, University College London, London, UK
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Mägi Reedik
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Kathy Ryan
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mark A Sarzynski
- Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Stephen Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | | | - Albert V Smith
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Icelandic Heart Association, Kópavogur, Iceland
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Emily Sonestedt
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Marin Strøm
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Faculty of Health Sciences, University of the Faroe Islands, Tórshavn, Faroe Islands
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Koon K Teo
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Angelo Tremblay
- Department of Kinesiology, Université Laval, Quebec, Quebec, Canada
- Centre Nutrition Santé et Société (NUTRISS), Institute of Nutrition and Functional Foods (INAF), Université Laval, Quebec, Quebec, Canada
| | - Andre G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jagadish Vangipurapu
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Natasja van Schoor
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, the Netherlands
| | - Uwe Völker
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Kayleen Williams
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Quenna Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kristin L Young
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Jian Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - M Carola Zillikens
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Science, National Instiute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Adam Ameur
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | | | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, NIHR Bristol Biomedical Research Center, University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, NIHR Bristol Biomedical Research Center, University of Bristol, Bristol, UK
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Louise Deldicque
- Faculty of Movement and Rehabilitation Sciences, Institute of Neuroscience, UC Louvain, Louvain-la-Neuve, Belgium
| | - Marcus Dörr
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Instiute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Caroline Fox
- Genetics and Pharmacogenomics (GpGx), Merck Research Labs, Boston, MA, USA
| | - Theodore Garland
- Department of Evolution, Ecology, and Organismal Biology, University of California, Riverside, Riverside, CA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kópavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Ulf Gyllensten
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Bernardo L Horta
- Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - Elina Hyppönen
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Population, Policy and Practice, Great Ormond Street Hospital Institute for Child Health, University College London, London, UK
| | - Marjo-Riitta Jarvelin
- Institute of Health Sciences, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics and HPA-MRC Center, School of Public Health, Imperial College London, London, UK
| | - W Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Lambertus A Kiemeney
- Radboud Institute for Health Sciences, Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Finnish Cardiovascular Research Center - Tampere, Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nicholas G Martin
- Mental Health and Neuroscience Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Mads Melbye
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- K.G.Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Center for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Andres Metspalu
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - David Meyre
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Claes Ohlsson
- Centre for Bone and Arthritis Research, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Albertine J Oldehinkel
- Interdisciplinary Center Psychopathology and Emotion Regulation, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Guillaume Pare
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Taesung Park
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea
- Department of Statistics, Seoul National University, Seoul, South Korea
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Tune H Pers
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ozren Polasek
- University of Split School of Medicine, Split, Croatia
| | - Inga Prokopenko
- Department of Clinical and Experimental Medicine, University of Surrey, Guilford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guilford, UK
- UMR 8199 - EGID, Institut Pasteur de Lille, CNRS, University of Lille, Lille, France
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, University of Bristol, Bristol, UK
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - Nathalie van der Velde
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
- Section of Geriatrics, Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Aging and Later Life, Amsterdam, the Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Peter Vollenweider
- Division of Internal Medicine, Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Greifswald, Greifswald, Germany
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Gérard Waeber
- Division of Internal Medicine, Department of Medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Heinz-Erich Wichmann
- Institute of Epidemiology, Helmholtz Zentrum München -Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Munich, Germany
| | - James F Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Andrea L Hevener
- Division of Endocrinology, Department of Medicine, University of California, Los Angeles, CA, USA
| | - Anna Krook
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Juleen R Zierath
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Martine A I Thomis
- Faculty of Movement and Rehabilitation Sciences, Department of Movement Sciences - Physical Activity, Sports & Health Research Group, KU Leuven, Leuven, Belgium
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marcel den Hoed
- The Beijer Laboratory and Department of Immunology, Genetics and Pathology, Uppsala University and SciLifeLab, Uppsala, Sweden.
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Viana RB, Morais SPD, Vancini RL, Andrade MS, Costa GDCT, Knechtle B, Nikolaidis PT, Lira CABD. EXERCISE SCIENCE IN HIGH SCHOOL BIOLOGY TEXTBOOKS. REV BRAS MED ESPORTE 2022. [DOI: 10.1590/1517-8692202228042021_0406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
ABSTRACT The content of high school textbooks related to physical activity and exercise is of utmost importance because physical activity and exercise are considered important tools in maintaining and improving health. Our objective was to analyze the presence and quality of exercise science content in high school biology textbooks approved by the National Textbook Plan. A guiding document was developed to enable the analysis of the textbooks. The topics investigated were: I) the extent of content related to exercise science; II) misconceptions about exercise science; III) health benefits attributed to exercise. The academic qualifications of the textbook authors were also analyzed. All analyzed textbooks (n = 9) featured some degree of exercise science content. In addition, ~67% of textbooks analyzed had at least one misconception regarding exercise science, the most common being related to biochemistry and muscle physiology. Also, 93.8% of the authors had undergraduate degrees in biological sciences; 43.8% had doctoral degrees. In conclusion, all high school biology textbooks presented content related to exercise science; however, most of them presented at least one misconception regarding exercise science. Thus, we suggest that the Brazilian National Textbook Plan should improve the criteria for analyzing biology textbooks. Level of Evidence III; Economic and decision analyses - Development of an economic or decision model.
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Affiliation(s)
- Ricardo Borges Viana
- Universidade Estadual de Goiás, Brazil; Faculdade Estácio de Sá de Goiás, Brazil
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Ramirez-Campillo R, Moran J, Oliver JL, Pedley JS, Lloyd RS, Granacher U. Programming Plyometric-Jump Training in Soccer: A Review. Sports (Basel) 2022; 10:sports10060094. [PMID: 35736834 PMCID: PMC9230747 DOI: 10.3390/sports10060094] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 05/25/2022] [Accepted: 06/07/2022] [Indexed: 12/26/2022] Open
Abstract
The aim of this review was to describe and summarize the scientific literature on programming parameters related to jump or plyometric training in male and female soccer players of different ages and fitness levels. A literature search was conducted in the electronic databases PubMed, Web of Science and Scopus using keywords related to the main topic of this study (e.g., “ballistic” and “plyometric”). According to the PICOS framework, the population for the review was restricted to soccer players, involved in jump or plyometric training. Among 7556 identified studies, 90 were eligible for inclusion. Only 12 studies were found for females. Most studies (n = 52) were conducted with youth male players. Moreover, only 35 studies determined the effectiveness of a given jump training programming factor. Based on the limited available research, it seems that a dose of 7 weeks (1−2 sessions per week), with ~80 jumps (specific of combined types) per session, using near-maximal or maximal intensity, with adequate recovery between repetitions (<15 s), sets (≥30 s) and sessions (≥24−48 h), using progressive overload and taper strategies, using appropriate surfaces (e.g., grass), and applied in a well-rested state, when combined with other training methods, would increase the outcome of effective and safe plyometric-jump training interventions aimed at improving soccer players physical fitness. In conclusion, jump training is an effective and easy-to-administer training approach for youth, adult, male and female soccer players. However, optimal programming for plyometric-jump training in soccer is yet to be determined in future research.
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Affiliation(s)
- Rodrigo Ramirez-Campillo
- Exercise and Rehabilitation Sciences Laboratory, School of Physical Therapy, Faculty of Rehabilitation Sciences, University Andres Bello, Santiago 7591538, Chile;
| | - Jason Moran
- School of Sport, Rehabilitation and Exercise Sciences, University of Essex, Essex CO4 3SQ, UK;
| | - Jon L. Oliver
- Youth Physical Development Centre, Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff CF23 6XD, UK; (J.L.O.); (J.S.P.); (R.S.L.)
| | - Jason S. Pedley
- Youth Physical Development Centre, Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff CF23 6XD, UK; (J.L.O.); (J.S.P.); (R.S.L.)
| | - Rhodri S. Lloyd
- Youth Physical Development Centre, Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff CF23 6XD, UK; (J.L.O.); (J.S.P.); (R.S.L.)
| | - Urs Granacher
- Division of Training and Movement Sciences, University of Potsdam, Am Neuen Palais 10, Building 12, 14469 Potsdam, Germany
- Correspondence:
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Varillas-Delgado D, Del Coso J, Gutiérrez-Hellín J, Aguilar-Navarro M, Muñoz A, Maestro A, Morencos E. Genetics and sports performance: the present and future in the identification of talent for sports based on DNA testing. Eur J Appl Physiol 2022; 122:1811-1830. [PMID: 35428907 PMCID: PMC9012664 DOI: 10.1007/s00421-022-04945-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 03/29/2022] [Indexed: 12/19/2022]
Abstract
The impact of genetics on physiology and sports performance is one of the most debated research aspects in sports sciences. Nearly 200 genetic polymorphisms have been found to influence sports performance traits, and over 20 polymorphisms may condition the status of the elite athlete. However, with the current evidence, it is certainly too early a stage to determine how to use genotyping as a tool for predicting exercise/sports performance or improving current methods of training. Research on this topic presents methodological limitations such as the lack of measurement of valid exercise performance phenotypes that make the study results difficult to interpret. Additionally, many studies present an insufficient cohort of athletes, or their classification as elite is dubious, which may introduce expectancy effects. Finally, the assessment of a progressively higher number of polymorphisms in the studies and the introduction of new analysis tools, such as the total genotype score (TGS) and genome-wide association studies (GWAS), have produced a considerable advance in the power of the analyses and a change from the study of single variants to determine pathways and systems associated with performance. The purpose of the present study was to comprehensively review evidence on the impact of genetics on endurance- and power-based exercise performance to clearly determine the potential utility of genotyping for detecting sports talent, enhancing training, or preventing exercise-related injuries, and to present an overview of recent research that has attempted to correct the methodological issues found in previous investigations.
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Affiliation(s)
- David Varillas-Delgado
- Faculty of Health Sciences, Universidad Francisco de Vitoria, Pozuelo de Alarcón, 28223, Madrid, Spain.
| | - Juan Del Coso
- Centre for Sport Studies, Rey Juan Carlos University, Fuenlabrada, 28933, Madrid, Spain
| | - Jorge Gutiérrez-Hellín
- Faculty of Health Sciences, Universidad Francisco de Vitoria, Pozuelo de Alarcón, 28223, Madrid, Spain
| | - Millán Aguilar-Navarro
- Faculty of Health Sciences, Universidad Francisco de Vitoria, Pozuelo de Alarcón, 28223, Madrid, Spain
| | - Alejandro Muñoz
- Faculty of Health Sciences, Universidad Francisco de Vitoria, Pozuelo de Alarcón, 28223, Madrid, Spain
| | | | - Esther Morencos
- Faculty of Health Sciences, Universidad Francisco de Vitoria, Pozuelo de Alarcón, 28223, Madrid, Spain
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Yang R, Jin F, Wang L, Shen X, Guo Q, Song H, Hu J, Zhao Q, Wan J, Cai M. Prediction and Identification of Power Performance Using Polygenic Models of Three Single-Nucleotide Polymorphisms in Chinese Elite Athletes. Front Genet 2021; 12:726552. [PMID: 34691150 PMCID: PMC8532995 DOI: 10.3389/fgene.2021.726552] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 09/09/2021] [Indexed: 02/02/2023] Open
Abstract
Objective: The manuscript aims to explore the relationship between power performance and SNPs of Chinese elite athletes and to create polygenic models. Methods: One hundred three Chinese elite athletes were divided into the power group (n = 60) and endurance group (n = 43) by their sports event. Best standing long jump (SLJ) and standing vertical jump (SVJ) were collected. Twenty SNPs were genotyped by SNaPshot. Genotype distribution and allele frequency were compared between groups. Additional genotype data of 125 Chinese elite athletes were used to verify the screened SNPs. Predictive and identifying models were established by multivariate logistic regression analysis. Results: ACTN3 (rs1815739), ADRB3 (rs4994), CNTFR (rs2070802), and PPARGC1A (rs8192678) were significantly different in genotype distribution or allele frequency between groups (p < 0.05). The predictive model consisted of ACTN3 (rs1815739), ADRB3 (rs4994), and PPARGC1A (rs8192678), the area under curve (AUC) of which was 0.736. The identifying model consisted of body mass index (BMI), standing vertical jump (SVJ), ACTN3, ADRB3, and PPARGC1A, the area under curve (AUC) of which was 0.854. Based on the two models, nomograms were created to visualize the results. Conclusion: Two models can be used for talent identification in Chinese athletes, among which the predictive model can be used in adolescent athletes to predict development potential of power performance and the identifying one can be used in elite athletes to evaluate power athletic status. These can be applied quickly and visually by using nomograms. When the score is more than the 130 or 148 cutoff, it suggests that the athlete has a good development potential or a high level for power performance.
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Affiliation(s)
- Ruoyu Yang
- College of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Feng Jin
- College of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Liyan Wang
- College of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Xunzhang Shen
- College of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.,Department of Talent Identification and Development, Shanghai Research Institute of Sports Science (Shanghai Anti-Doping Center), Shanghai, China
| | - Qi Guo
- College of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Haihan Song
- Central Lab, Shanghai Pudong New Area People's Hospital, Shanghai, China
| | - Jingyun Hu
- Central Lab, Shanghai Pudong New Area People's Hospital, Shanghai, China
| | - Qiang Zhao
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jian Wan
- Department of Emergency and Critical Care Medicine, Shanghai Pudong New Area People's Hospital, Shanghai, China
| | - Ming Cai
- Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China
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10
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Kent JA, Hayes KL. Exercise Physiology From 1980 to 2020: Application of the Natural Sciences. KINESIOLOGY REVIEW (CHAMPAIGN, ILL.) 2021; 10:238-247. [PMID: 35464337 PMCID: PMC9022627 DOI: 10.1123/kr.2021-0024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The field of exercise physiology has enjoyed tremendous growth in the past 40 years. With its foundations in the natural sciences, it is an interdisciplinary field that is highly relevant to human performance and health. The focus of this review is on highlighting new approaches, knowledge, and opportunities that have emerged in exercise physiology over the last four decades. Key among these is the adoption of advanced technologies by exercise physiologists to address fundamental research questions, and the expansion of research topics to range from molecular to organismal, and population scales in order to clarify the underlying mechanisms and impact of physiological responses to exercise in health and disease. Collectively, these advances have ensured the position of the field as a partner in generating new knowledge across many scientific and health disciplines.
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Affiliation(s)
- Jane A Kent
- Muscle Physiology Laboratory, Department of Kinesiology, University of Massachusetts Amherst, Amherst, Massachusetts, USA
| | - Kate L Hayes
- Muscle Physiology Laboratory, Department of Kinesiology, University of Massachusetts Amherst, Amherst, Massachusetts, USA
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11
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Navas-Carretero S, San-Cristobal R, Alvarez-Alvarez I, Celis-Morales C, Livingstone KM, O'Donovan CB, Mavrogianni C, Lambrinou CP, Manios Y, Traczyck I, Drevon CA, Marsaux CFM, Saris WHM, Fallaize R, Macready AL, Lovegrove JA, Gundersen TE, Walsh M, Brennan L, Gibney ER, Gibney M, Mathers JC, Martinez JA. Interactions of Carbohydrate Intake and Physical Activity with Regulatory Genes Affecting Glycaemia: A Food4Me Study Analysis. Lifestyle Genom 2021; 14:63-72. [PMID: 34186541 DOI: 10.1159/000515068] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 02/04/2021] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Carbohydrate intake and physical activity are related to glucose homeostasis, both being influenced by individual genetic makeup. However, the interactions between these 2 factors, as affected by genetics, on glycaemia have been scarcely reported. OBJECTIVE We focused on analysing the interplay between carbohydrate intake and physical activity levels on blood glucose, taking into account a genetic risk score (GRS), based on SNPs related to glucose/energy metabolism. METHODS A total of 1,271 individuals from the Food4Me cohort, who completed the nutritional intervention, were evaluated at baseline. We collected dietary information by using an online-validated food frequency questionnaire, a questionnaire on physical activity, blood biochemistry by analysis of dried blood spots, and by analysis of selected SNPs. Fifteen out of 31 SNPs, with recognized participation in carbohydrate/energy metabolism, were included in the component analyses. The GRS included risk alleles involved in the control of glycaemia or energy-yielding processes. RESULTS Data concerning anthropometric, clinical, metabolic, dietary intake, physical activity, and genetics related to blood glucose levels showed expected trends in European individuals of comparable sex and age, being categorized by lifestyle, BMI, and energy/carbohydrate intakes, in this Food4Me population. Blood glucose was inversely associated with physical activity level (β = -0.041, p = 0.013) and positively correlated with the GRS values (β = 0.015, p = 0.047). Interestingly, an interaction affecting glycaemia, concerning physical activity level with carbohydrate intake, was found (β = -0.060, p = 0.033), which also significantly depended on the genetic background (GRS). CONCLUSIONS The relationships of carbohydrate intake and physical activity are important in understanding glucose homeostasis, where a role for the genetic background should be ascribed.
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Affiliation(s)
- Santiago Navas-Carretero
- Centre for Nutrition Research, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.,CIBEROBN, Instituto de Salud Carlos III, Madrid, Spain.,IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Rodrigo San-Cristobal
- Centre for Nutrition Research, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
| | - Ismael Alvarez-Alvarez
- Centre for Nutrition Research, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
| | - Carlos Celis-Morales
- Human Nutrition Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom.,BHF Glasgow cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Katherine M Livingstone
- Human Nutrition Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom.,Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
| | - Claire B O'Donovan
- UCD Institute of Food and Health, University College Dublin, Belfield, Dublin, Ireland
| | | | | | - Yannis Manios
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
| | - Iwona Traczyck
- Department of Human Nutrition, Faculty of Health Sciences, Medical University of Warsaw, Warsaw, Poland
| | - Christian A Drevon
- Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Cyril F M Marsaux
- Department of Human Biology, NUTRIM, School for Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Wim H M Saris
- Department of Human Biology, NUTRIM, School for Nutrition and Translational Research in Metabolism, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Rosalind Fallaize
- School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom.,Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, United Kingdom
| | - Anna L Macready
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, United Kingdom
| | - Julie A Lovegrove
- Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, United Kingdom
| | | | - Marianne Walsh
- UCD Institute of Food and Health, University College Dublin, Belfield, Dublin, Ireland
| | - Lorraine Brennan
- UCD Institute of Food and Health, University College Dublin, Belfield, Dublin, Ireland
| | - Eileen R Gibney
- UCD Institute of Food and Health, University College Dublin, Belfield, Dublin, Ireland
| | - Mike Gibney
- UCD Institute of Food and Health, University College Dublin, Belfield, Dublin, Ireland
| | - John C Mathers
- Human Nutrition Research Centre, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - J Alfredo Martinez
- Centre for Nutrition Research, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.,CIBEROBN, Instituto de Salud Carlos III, Madrid, Spain.,IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
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12
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Ducret V, Richards AJ, Videlier M, Scalvenzi T, Moore KA, Paszkiewicz K, Bonneaud C, Pollet N, Herrel A. Transcriptomic analysis of the trade-off between endurance and burst-performance in the frog Xenopus allofraseri. BMC Genomics 2021; 22:204. [PMID: 33757428 PMCID: PMC7986297 DOI: 10.1186/s12864-021-07517-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 03/08/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Variation in locomotor capacity among animals often reflects adaptations to different environments. Despite evidence that physical performance is heritable, the molecular basis of locomotor performance and performance trade-offs remains poorly understood. In this study we identify the genes, signaling pathways, and regulatory processes possibly responsible for the trade-off between burst performance and endurance observed in Xenopus allofraseri, using a transcriptomic approach. RESULTS We obtained a total of about 121 million paired-end reads from Illumina RNA sequencing and analyzed 218,541 transcripts obtained from a de novo assembly. We identified 109 transcripts with a significant differential expression between endurant and burst performant individuals (FDR ≤ 0.05 and logFC ≥2), and blast searches resulted in 103 protein-coding genes. We found major differences between endurant and burst-performant individuals in the expression of genes involved in the polymerization and ATPase activity of actin filaments, cellular trafficking, proteoglycans and extracellular proteins secreted, lipid metabolism, mitochondrial activity and regulators of signaling cascades. Remarkably, we revealed transcript isoforms of key genes with functions in metabolism, apoptosis, nuclear export and as a transcriptional corepressor, expressed in either burst-performant or endurant individuals. Lastly, we find two up-regulated transcripts in burst-performant individuals that correspond to the expression of myosin-binding protein C fast-type (mybpc2). This suggests the presence of mybpc2 homoeologs and may have been favored by selection to permit fast and powerful locomotion. CONCLUSION These results suggest that the differential expression of genes belonging to the pathways of calcium signaling, endoplasmic reticulum stress responses and striated muscle contraction, in addition to the use of alternative splicing and effectors of cellular activity underlie locomotor performance trade-offs. Ultimately, our transcriptomic analysis offers new perspectives for future analyses of the role of single nucleotide variants, homoeology and alternative splicing in the evolution of locomotor performance trade-offs.
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Affiliation(s)
- Valérie Ducret
- UMR 7179 MECADEV, C.N.R.S/M.N.H.N., Département Adaptations du Vivant, 55 Rue Buffon, 75005, Paris, France.
| | - Adam J Richards
- Station d'Ecologie Expérimentale du CNRS, USR 2936, 09200, Moulis, France
| | - Mathieu Videlier
- Functional Ecology Lab, Department of Biology, University of Ottawa, 30 Marie Curie, Ottawa, ON, K1N 6N5, Canada
| | - Thibault Scalvenzi
- Evolution, Génomes, Comportement & Ecologie, Université Paris-Saclay, CNRS, IRD, 91198, Gif-sur-Yvette, France
| | - Karen A Moore
- Exeter Sequencing Service, College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4QD, UK
| | - Konrad Paszkiewicz
- Exeter Sequencing Service, College of Life and Environmental Sciences, University of Exeter, Exeter, EX4 4QD, UK
| | - Camille Bonneaud
- Station d'Ecologie Expérimentale du CNRS, USR 2936, 09200, Moulis, France
- Centre for Ecology & Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn, Cornwall, UK
| | - Nicolas Pollet
- Evolution, Génomes, Comportement & Ecologie, Université Paris-Saclay, CNRS, IRD, 91198, Gif-sur-Yvette, France
| | - Anthony Herrel
- Station d'Ecologie Expérimentale du CNRS, USR 2936, 09200, Moulis, France
- Evolutionary Morphology of Vertebrates, Ghent University, B-9000, Ghent, Belgium
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13
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Bartolomé E, Perdomo-González DI, Sánchez-Guerrero MJ, Valera M. Genetic Parameters of Effort and Recovery in Sport Horses Assessed with Infrared Thermography. Animals (Basel) 2021; 11:ani11030832. [PMID: 33809482 PMCID: PMC8001494 DOI: 10.3390/ani11030832] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 03/08/2021] [Accepted: 03/12/2021] [Indexed: 12/05/2022] Open
Abstract
Simple Summary The way a horse activates (effort phase-EP) and recovers (recovery phase-RP) during a sport event can affect its sport performance. The aim of this manuscript was to test horses’ adaptation to sport performance and its genetic basis, using eye temperature assessed with infrared thermography. EP and RP were measured in 495 Spanish Sport Horses, during a performance test, considering sex (2) and genetic lines (5) as fixed effects. The ranking position obtained on the official sport competition celebrated the day after the performance test was also collected. Differences in variables due to genetic line and sex effects were found, showing that, regardless of the genetic line, stallions tended to recover better than mares after the sport test developed. High positive correlations were found between EP and RP for both fixed effects, so that, the higher the EP, the higher the RP. However, for the ranking position, a low negative correlation was found, so that the higher the eye temperature increase, the better the position. Heritabilities showed medium–high values with a medium positive genetic correlation between them. Thus, breed origins and sex influence horses’ effort and recovery during sport performance, showing a genetic basis adequate for selection. Abstract The way a horse activates (effort phase-EP) and recovers (recovery phase-RP) during a sport event can affect its sport performance. The aim of this manuscript was to test horses’ adaptation to sport performance and its genetic basis, using eye temperature assessed with infrared thermography. EP and RP were measured in 495 Spanish Sport Horses, during a performance test, considering sex (2) and genetic lines (5) as fixed effects. The ranking position obtained on an official sport competition was also collected. Differences in variables due to genetic line and sex effects were found, showing that, regardless of the genetic line, stallions tended to recover better than mares after the sport test developed. High positive intra-class correlations (p < 0.001) were found between EP and RP for both fixed effects, so that the higher the EP, the higher the RP. However, for the ranking position, a low negative correlation (p < 0.01) was found, so that the higher the eye temperature increase, the better the position. Heritabilities showed medium–high values with a medium positive genetic correlation between them. Thus, breed origins and sex influence horses’ effort and recovery during sport performance, showing a genetic basis adequate for selection.
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14
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Reguero M, Gómez de Cedrón M, Reglero G, Quintela JC, Ramírez de Molina A. Natural Extracts to Augment Energy Expenditure as a Complementary Approach to Tackle Obesity and Associated Metabolic Alterations. Biomolecules 2021; 11:biom11030412. [PMID: 33802173 PMCID: PMC7999034 DOI: 10.3390/biom11030412] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 03/03/2021] [Accepted: 03/08/2021] [Indexed: 12/12/2022] Open
Abstract
Obesity is the epidemic of the 21st century. In developing countries, the prevalence of obesity continues to rise, and obesity is occurring at younger ages. Obesity and associated metabolic stress disrupt the whole-body physiology. Adipocytes are critical components of the systemic metabolic control, functioning as an endocrine organ. The enlarged adipocytes during obesity recruit macrophages promoting chronic inflammation and insulin resistance. Together with the genetic susceptibility (single nucleotide polymorphisms, SNP) and metabolic alterations at the molecular level, it has been highlighted that key modifiable risk factors, such as those related to lifestyle, contribute to the development of obesity. In this scenario, urgent therapeutic options are needed, including not only pharmacotherapy but also nutrients, bioactive compounds, and natural extracts to reverse the metabolic alterations associated with obesity. Herein, we first summarize the main targetable processes to tackle obesity, including activation of thermogenesis in brown adipose tissue (BAT) and in white adipose tissue (WAT-browning), and the promotion of energy expenditure and/or fatty acid oxidation (FAO) in muscles. Then, we perform a screening of 20 natural extracts (EFSA approved) to determine their potential in the activation of FAO and/or thermogenesis, as well as the increase in respiratory capacity. By means of innovative technologies, such as the study of their effects on cell bioenergetics (Seahorse bioanalyzer), we end up with the selection of four extracts with potential application to ameliorate the deleterious effects of obesity and the chronic associated inflammation.
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Affiliation(s)
- Marina Reguero
- Molecular Oncology Group, Precision Nutrition and Health, IMDEA Food Institute, CEI UAM + CSIC, Ctra. de Cantoblanco 8, 28049 Madrid, Spain;
- NATAC BIOTECH, Electronica 7, 28923 Madrid, Spain;
| | - Marta Gómez de Cedrón
- Molecular Oncology Group, Precision Nutrition and Health, IMDEA Food Institute, CEI UAM + CSIC, Ctra. de Cantoblanco 8, 28049 Madrid, Spain;
- Correspondence: (M.G.d.C.); (A.R.d.M.)
| | - Guillermo Reglero
- Production and Characterization of Novel Foods Department, Institute of Food Science Research CIAL, CEI UAM + CSIC, 28049 Madrid, Spain;
| | | | - Ana Ramírez de Molina
- Molecular Oncology Group, Precision Nutrition and Health, IMDEA Food Institute, CEI UAM + CSIC, Ctra. de Cantoblanco 8, 28049 Madrid, Spain;
- Correspondence: (M.G.d.C.); (A.R.d.M.)
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15
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Hillis DA, Yadgary L, Weinstock GM, Pardo-Manuel de Villena F, Pomp D, Fowler AS, Xu S, Chan F, Garland T. Genetic Basis of Aerobically Supported Voluntary Exercise: Results from a Selection Experiment with House Mice. Genetics 2020; 216:781-804. [PMID: 32978270 PMCID: PMC7648575 DOI: 10.1534/genetics.120.303668] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 09/18/2020] [Indexed: 12/14/2022] Open
Abstract
The biological basis of exercise behavior is increasingly relevant for maintaining healthy lifestyles. Various quantitative genetic studies and selection experiments have conclusively demonstrated substantial heritability for exercise behavior in both humans and laboratory rodents. In the "High Runner" selection experiment, four replicate lines of Mus domesticus were bred for high voluntary wheel running (HR), along with four nonselected control (C) lines. After 61 generations, the genomes of 79 mice (9-10 from each line) were fully sequenced and single nucleotide polymorphisms (SNPs) were identified. We used nested ANOVA with MIVQUE estimation and other approaches to compare allele frequencies between the HR and C lines for both SNPs and haplotypes. Approximately 61 genomic regions, across all somatic chromosomes, showed evidence of differentiation; 12 of these regions were differentiated by all methods of analysis. Gene function was inferred largely using Panther gene ontology terms and KO phenotypes associated with genes of interest. Some of the differentiated genes are known to be associated with behavior/motivational systems and/or athletic ability, including Sorl1, Dach1, and Cdh10 Sorl1 is a sorting protein associated with cholinergic neuron morphology, vascular wound healing, and metabolism. Dach1 is associated with limb bud development and neural differentiation. Cdh10 is a calcium ion binding protein associated with phrenic neurons. Overall, these results indicate that selective breeding for high voluntary exercise has resulted in changes in allele frequencies for multiple genes associated with both motivation and ability for endurance exercise, providing candidate genes that may explain phenotypic changes observed in previous studies.
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Affiliation(s)
- David A Hillis
- Genetics, Genomics, and Bioinformatics Graduate Program, University of California, Riverside, California 92521
| | - Liran Yadgary
- Department of Genetics, University of North Carolina at Chapel Hill, North Carolina 27599
| | - George M Weinstock
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032
| | | | - Daniel Pomp
- Department of Genetics, University of North Carolina at Chapel Hill, North Carolina 27599
| | - Alexandra S Fowler
- Department of Evolution, Ecology, and Organismal Biology, University of California, Riverside, California 92521
| | - Shizhong Xu
- Department of Botany and Plant Sciences, University of California, Riverside, California 92521
| | - Frank Chan
- Friedrich Miescher Laboratory of the Max Planck Society, 72076 Tübingen, Germany
| | - Theodore Garland
- Department of Evolution, Ecology, and Organismal Biology, University of California, Riverside, California 92521
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16
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Denham J, McCluskey M, Denham MM, Sellami M, Davie AJ. Epigenetic control of exercise adaptations in the equine athlete: Current evidence and future directions. Equine Vet J 2020; 53:431-450. [PMID: 32671871 DOI: 10.1111/evj.13320] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 06/04/2020] [Accepted: 06/25/2020] [Indexed: 12/11/2022]
Abstract
Horses (Equus ferus caballus) have evolved over the past 300 years in response to man-made selection for particular athletic traits. Some of the selected traits were selected based on the size and horses' muscular power (eg Clydesdales), whereas other breeds were bred for peak running performance (eg Thoroughbred and Arabian). Although the physiological changes and some of the cellular adaptations responsible for athletic potential of horses have been identified, the molecular mechanisms are only just beginning to be comprehensively investigated. The purpose of this review was to outline and discuss the current understanding of the molecular mechanisms underpinning the athletic performance and cardiorespiratory fitness in athletic breeds of horses. A brief review of the biology of epigenetics is provided, including discussion on DNA methylation, histone modifications and small RNAs, followed by a summary and critical review of the current work on the exercise-induced epigenetic and transcriptional changes in horses. Important unanswered questions and currently unexplored areas that deserve attention are highlighted. Finally, a rationale for the analysis of epigenetic modifications in the context with exercise-related traits and ailments associated with athletic breeds of horses is outlined in order to help guide future research.
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Affiliation(s)
- Joshua Denham
- RMIT University, School of Health and Biomedical Sciences, Melbourne, VIC, Australia
| | | | | | - Maha Sellami
- Qatar University, College of Arts and Sciences (CAS), Sport Science Program (SSP), Doha, Qatar
| | - Allan J Davie
- Australian Equine Racing and Research Centre (AERR), Ballina, NSW, Australia
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17
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Riddle NC. Variation in the response to exercise stimulation in Drosophila: marathon runner versus sprinter genotypes. J Exp Biol 2020; 223:jeb229997. [PMID: 32737212 DOI: 10.1242/jeb.229997] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 07/27/2020] [Indexed: 12/13/2022]
Abstract
Animals' behaviors vary in response to their environment, both biotic and abiotic. These behavioral responses have significant impacts on animal survival and fitness, and thus, many behavioral responses are at least partially under genetic control. In Drosophila, for example, genes impacting aggression, courtship behavior, circadian rhythms and sleep have been identified. Animal activity also is influenced strongly by genetics. My lab previously has used the Drosophila melanogaster Genetics Reference Panel (DGRP) to investigate activity levels and identified over 100 genes linked to activity. Here, I re-examined these data to determine whether Drosophila strains differ in their response to rotational exercise stimulation, not simply in the amount of activity, but in activity patterns and timing of activity. Specifically, I asked whether there are fly strains exhibiting either a 'marathoner' pattern of activity, i.e. remaining active throughout the 2 h exercise period, or a 'sprinter' pattern, i.e. carrying out most of the activity early in the exercise period. The DGRP strains examined differ significantly in how much activity is carried out at the beginning of the exercise period, and this pattern is influenced by both sex and genotype. Interestingly, there was no clear link between the activity response pattern and lifespan of the animals. Using genome-wide association studies (GWAS), I identified 10 high confidence candidate genes that control the degree to which Drosophila exercise behaviors fit a marathoner or sprinter activity pattern. This finding suggests that, similar to other aspects of locomotor behavior, the timing of activity patterns in response to exercise stimulation is under genetic control.
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Affiliation(s)
- Nicole C Riddle
- Department of Biology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
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18
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Kelly RS, Kelly MP, Kelly P. Metabolomics, physical activity, exercise and health: A review of the current evidence. Biochim Biophys Acta Mol Basis Dis 2020; 1866:165936. [PMID: 32827647 DOI: 10.1016/j.bbadis.2020.165936] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 08/12/2020] [Accepted: 08/14/2020] [Indexed: 01/09/2023]
Abstract
Physical activity (PA) and exercise are among the most important determinants of health. However, PA is a complex and heterogeneous behavior and the biological mechanisms through which it impacts individuals and populations in different ways are not well understood. Genetics and environment likely play pivotal roles but further work is needed to understand their relative contributions and how they may be mediated. Metabolomics offers a promising approach to explore these relationships. In this review, we provide a comprehensive appraisal of the PA-metabolomics literature to date. This overwhelmingly supports the hypothesis of a metabolomic response to PA, which can differ between groups and individuals. It also suggests a biological gradient in this response based on PA intensity, with some evidence for global longer-term changes in the metabolome of highly active individuals. However, many questions remain and we conclude by highlighting future critical research avenues to help elucidate the role of PA in the maintenance of health and the development of disease.
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Affiliation(s)
- Rachel S Kelly
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Michael P Kelly
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Forvie Site, Cambridge CB2 0SR. UK.
| | - Paul Kelly
- Physical Activity for Health Research Center (PAHRC), University of Edinburgh, St Leonard's Land, Edinburgh EH8 8AQ, UK.
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19
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Tanisawa K, Wang G, Seto J, Verdouka I, Twycross-Lewis R, Karanikolou A, Tanaka M, Borjesson M, Di Luigi L, Dohi M, Wolfarth B, Swart J, Bilzon JLJ, Badtieva V, Papadopoulou T, Casasco M, Geistlinger M, Bachl N, Pigozzi F, Pitsiladis Y. Sport and exercise genomics: the FIMS 2019 consensus statement update. Br J Sports Med 2020; 54:969-975. [PMID: 32201388 PMCID: PMC7418627 DOI: 10.1136/bjsports-2019-101532] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/17/2019] [Indexed: 12/26/2022]
Abstract
Rapid advances in technologies in the field of genomics such as high throughput DNA sequencing, big data processing by machine learning algorithms and gene-editing techniques are expected to make precision medicine and gene-therapy a greater reality. However, this development will raise many important new issues, including ethical, moral, social and privacy issues. The field of exercise genomics has also advanced by incorporating these innovative technologies. There is therefore an urgent need for guiding references for sport and exercise genomics to allow the necessary advancements in this field of sport and exercise medicine, while protecting athletes from any invasion of privacy and misuse of their genomic information. Here, we update a previous consensus and develop a guiding reference for sport and exercise genomics based on a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis. This SWOT analysis and the developed guiding reference highlight the need for scientists/clinicians to be well-versed in ethics and data protection policy to advance sport and exercise genomics without compromising the privacy of athletes and the efforts of international sports federations. Conducting research based on the present guiding reference will mitigate to a great extent the risks brought about by inappropriate use of genomic information and allow further development of sport and exercise genomics in accordance with best ethical standards and international data protection principles and policies. This guiding reference should regularly be updated on the basis of new information emerging from the area of sport and exercise medicine as well as from the developments and challenges in genomics of health and disease in general in order to best protect the athletes, patients and all other relevant stakeholders.
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Affiliation(s)
- Kumpei Tanisawa
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan
| | - Guan Wang
- Collaborating Centre of Sports Medicine, University of Brighton, Eastbourne, UK
| | - Jane Seto
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
| | - Ioanna Verdouka
- Collaborating Centre of Sports Medicine, University of Brighton, Eastbourne, UK
| | - Richard Twycross-Lewis
- School of Engineering and Materials Science, Queen Mary University of London, London, UK
| | - Antonia Karanikolou
- Collaborating Centre of Sports Medicine, University of Brighton, Eastbourne, UK
| | - Masashi Tanaka
- Department for Health and Longevity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
| | - Mats Borjesson
- Department of Neuroscience and Physiology, Center for Health and Performance, Goteborg University, Göteborg, Sweden
- Sahlgrenska University Hospital/Ostra, Göteborg, Sweden
| | - Luigi Di Luigi
- Unit of Endocrinology, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Rome, Italy
| | - Michiko Dohi
- Sport Medical Center, Japan Institute of Sports Sciences, Tokyo, Japan
| | - Bernd Wolfarth
- Department of Sport Medicine, Humboldt University and Charité University School of Medicine, Berlin, Germany
| | - Jeroen Swart
- UCT Research Unit for Exercise Science and Sports Medicine, Cape Town, South Africa
| | | | - Victoriya Badtieva
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of Russia, Moscow, Russian Federation
- Moscow Research and Practical Center for Medical Rehabilitation, Restorative and Sports Medicine, Moscow Healthcare Department, Moscow, Russian Federation
| | - Theodora Papadopoulou
- Defence Medical Rehabilitation Centre, Stanford Hall, Loughborough, UK
- British Association of Sport and Exercise Medicine, Doncaster, UK
| | | | - Michael Geistlinger
- Unit of International Law, Department of Constitutional, International and European Law, University of Salzburg, Salzburg, Salzburg, Austria
| | - Norbert Bachl
- Institute of Sports Science, University of Vienna, Vienna, Austria
- Austrian Institute of Sports Medicine, Vienna, Austria
| | - Fabio Pigozzi
- Sport Medicine Unit, Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Rome, Italy
| | - Yannis Pitsiladis
- Collaborating Centre of Sports Medicine, University of Brighton, Eastbourne, UK
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20
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Effect of ACTN3 Genotype on Sports Performance, Exercise-Induced Muscle Damage, and Injury Epidemiology. Sports (Basel) 2020; 8:sports8070099. [PMID: 32668587 PMCID: PMC7404684 DOI: 10.3390/sports8070099] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 06/30/2020] [Accepted: 07/09/2020] [Indexed: 12/20/2022] Open
Abstract
Genetic factors play a significant role in athletic performance and its related phenotypes such as power, strength and aerobic capacity. In this regard, the lack of a muscle protein due to a genetic polymorphism has been found to affect sport performance in a wide variety of ways. α-actinin-3 is a protein located within the skeletal muscle with a key role in the production of sarcomeric force. A common stop-codon polymorphism (rs1815739; R577X) in the gene that codes for α-actinin-3 (ACTN3) produces individuals with the XX genotype that lack expression of a functional α-actinin-3. In contrast, individuals with the R-allele (i.e., RX vs. RR genotypes) in this polymorphism can express α-actinin-3. Interestingly, around ~18% of the world population have the XX genotype and much has been debated about why a polymorphism that produces a lack of a muscle protein has endured natural selection. Several investigations have found that α-actinin-3 deficiency due to XX homozygosity in the ACTN3 R577X polymorphism can negatively affect sports performance through several structural, metabolic, or signaling changes. In addition, new evidence suggests that α-actinin-3 deficiency may also impact sports performance through indirect factors such a higher risk for injury or lower resistance to muscle-damaging exercise. The purpose of this discussion is to provide a clear explanation of the effect of α-actinin-3 deficiency due to the ACTN3 XX genotype on sport. Key focus has been provided about the effect of α-actinin-3 deficiency on morphologic changes in skeletal muscle, on the low frequency of XX athletes in some athletic disciplines, and on injury epidemiology.
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21
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Clos E, Pruna R, Lundblad M, Artells R, Maffulli N. ACTN3's R577X Single Nucleotide Polymorphism Allele Distribution Differs Significantly in Professional Football Players according to Their Field Position. Med Princ Pract 2020; 30:92-97. [PMID: 32492691 PMCID: PMC7923889 DOI: 10.1159/000509089] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 06/01/2020] [Indexed: 01/13/2023] Open
Abstract
INTRODUCTION Football is characterised by intermittent high-intensity efforts varying according to the field position of a player. We aimed to ascertain whether polymorphisms in the ACTN3 gene are associated with different playing positions in elite professional football players. SUBJECTS AND METHODS Genotyping of the ACTN3 gene was conducted in 43 elite professional football players of a single team. Playing position was recorded based on the player's most frequent position. RESULTS The genotype distribution was not significant between positions (p = 0.057), while the allele distribution differed significantly (p = 0.035). Goalkeepers (p = 0.04, p = 0.03), central defenders (p = 0.03, p = 0.01), and central midfielders (p = 0.01, p = 0.00) had a significantly different allele distribution compared with wide midfielders and forward players. CONCLUSIONS Genetic biomarkers may be important when analysing performance capability in elite professional football. Identifying the genetic characteristics of a player to adapt his playing position may lead to orientation of positions based on physical capabilities and tissue quality in young football players, and also to performance enhancement in those who are already playing in professional teams.
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Affiliation(s)
- Enric Clos
- Girona FC Medical Services, Girona, Spain,
| | - Ricard Pruna
- FC Barcelona Medical Services, FIFA Medical Centre of Excellence, Barcelona, Spain
| | - Matilda Lundblad
- Sahlgrenska Academy Institute of Clinical Sciences, Gothenburg University, Gothenburg, Sweden
| | | | - Nicola Maffulli
- Department of Musculoskeletal Disorders, School of Medicine and Surgery, University of Salerno, Salerno, Italy
- Clinica Ortopedica, Ospedale San Giovanni di Dio e Ruggi D'Aragona, Salerno, Italy
- Queen Mary University of London, Barts and the London School of Medicine and Dentistry, Centre for Sports and Exercise Medicine, Mile End Hospital, London, United Kingdom
- Keele University, School of Medicine, Institute of Science and Technology in Medicine, Guy Hilton Research Centre, Hartshill, United Kingdom
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22
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Caru M, Curnier D. Sex and Gender Considerations After Surviving Acute Lymphoblastic Leukemia: An Exercise Oncology Context. J Adolesc Young Adult Oncol 2020; 9:441-444. [DOI: 10.1089/jayao.2019.0137] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Affiliation(s)
- Maxime Caru
- Laboratory of Pathophysiology of Exercise (LPEX), School of Kinesiology and Physical Activity Sciences, Faculty of Medicine, University of Montreal, Montreal, Canada
- Sainte-Justine University Health Center, Research Center, Montreal, Canada
- Laboratoire EA 4430–Clinique Psychanalyse Developpement (CliPsyD), University of Paris Nanterre, Nanterre, France
| | - Daniel Curnier
- Laboratory of Pathophysiology of Exercise (LPEX), School of Kinesiology and Physical Activity Sciences, Faculty of Medicine, University of Montreal, Montreal, Canada
- Sainte-Justine University Health Center, Research Center, Montreal, Canada
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23
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Su J, Wang H, Tian Y, Hu H, Gu W, Zhang T, Li M, Shen C, Gu HF. Impact of physical exercise intervention and PPARγ genetic polymorphisms on cardio-metabolic parameters among a Chinese youth population. BMJ Open Sport Exerc Med 2020; 6:e000681. [PMID: 32341796 PMCID: PMC7173993 DOI: 10.1136/bmjsem-2019-000681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/08/2020] [Indexed: 11/24/2022] Open
Abstract
Objective Physical inactivity inChinese youth students particularly in senior high schools, who participate inthe National Higher Education Entrance Examination (NCEE) is very common. Inorder to explore the beneficial effects from physical exercise and education afterNCEE, we performed a Physicalexercise Intervention Program in the Youth (PiPy) to evaluate the interaction with PPARγ genetic variants on cardiovascular and metabolicparameters. Methods A total of 772 freshmen (males 610/females162) from high schools to university were recruited into the PiPy cohort, which was designedaccording to the National Student Health Standards in China. Anthropometric data were collected, whilephysical activities and body composition at the baseline of PiPy cohort weremeasured with SECAprotocols. Eighttagged single nucleotide polymorphisms (SNPs) in the PPARγ gene were genotyped with TaqMan allelicdiscrimination. Results After physical exercise intervention forthree months, in parallel with increased physical activities, BMI and skeletalmuscle content in all subjects was enhanced, while heart rate and bloodpressures were decreased. Furthermore, SNPs in 5’-UTR of the PPARγ gene, including rs2920502, rs9817428 and rs2972164, were found to be associated with the changes of BMI. Body weight in the subjects with BMI <18.5and 18.5-23.9 kg/m2 were increased, while the obese subjects (BMI ≥24.0 kg/m2) decreased. Conclusion The present study for the first timedemonstrated that the PiPy could improve cardio-metabolic parameters such asheart rate, blood pressures and BMI for Chinese youth students after NCEE, inwhich the genetic interactive effects of PPARγ should be included into obesityintervention.
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Affiliation(s)
- Juan Su
- Department of Physical Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Hui Wang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yuanrui Tian
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Haixu Hu
- Department of Physical Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Wanjian Gu
- Department of Clinical Laboratory, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Ting Zhang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Mengxia Li
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chong Shen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Harvest F Gu
- Center for Pathophysiology, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
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24
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Microfluidic Quantitative PCR Detection of 12 Transgenes from Horse Plasma for Gene Doping Control. Genes (Basel) 2020; 11:genes11040457. [PMID: 32340130 PMCID: PMC7230449 DOI: 10.3390/genes11040457] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 04/13/2020] [Accepted: 04/20/2020] [Indexed: 12/18/2022] Open
Abstract
Gene doping, an activity which abuses and misuses gene therapy, is a major concern in sports and horseracing industries. Effective methods capable of detecting and monitoring gene doping are urgently needed. Although several PCR-based methods that detect transgenes have been developed, many of them focus only on a single transgene. However, numerous genes associated with athletic ability may be potential gene-doping material. Here, we developed a detection method that targets multiple transgenes. We targeted 12 genes that may be associated with athletic performance and designed two TaqMan probe/primer sets for each one. A panel of 24 assays was prepared and detected via a microfluidic quantitative PCR (MFQPCR) system using integrated fluidic circuits (IFCs). The limit of detection of the panel was 6.25 copy/μL. Amplification-specificity was validated using several concentrations of reference materials and animal genomic DNA, leading to specific detection. In addition, target-specific detection was successfully achieved in a horse administered 20 mg of the EPO transgene via MFQPCR. Therefore, MFQPCR may be considered a suitable method for multiple-target detection in gene-doping control. To our knowledge, this is the first application of microfluidic qPCR (MFQPCR) for gene-doping control in horseracing.
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25
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Ramirez‐Campillo R, Moran J, Chaabene H, Granacher U, Behm DG, García‐Hermoso A, Izquierdo M. Methodological characteristics and future directions for plyometric jump training research: A scoping review update. Scand J Med Sci Sports 2020; 30:983-997. [DOI: 10.1111/sms.13633] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 01/08/2020] [Accepted: 02/04/2020] [Indexed: 01/22/2023]
Affiliation(s)
- Rodrigo Ramirez‐Campillo
- Laboratory of Human Performance. Quality of Life and Wellness Research Group Department of Physical Activity Sciences Universidad de Los Lagos Osorno Chile
- Centro de Investigación en Fisiología del Ejercicio Universidad Mayor Santiago Chile
| | - Jason Moran
- School of Sport, Rehabilitation and Exercise Sciences University of Essex Colchester UK
| | - Helmi Chaabene
- Division of Training and Movement Sciences Research Focus Cognitive Sciences University of Potsdam Potsdam Germany
- High Institute of Sports and Physical Education Kef University of Jendouba Jendouba Tunisia
| | - Urs Granacher
- Division of Training and Movement Sciences Research Focus Cognitive Sciences University of Potsdam Potsdam Germany
| | - David G. Behm
- School of Human Kinetics and Recreation Memorial University of Newfoundland St. John’s Canada
| | - Antonio García‐Hermoso
- Navarrabiomed Complejo Hospitalario de Navarra (CHN) IdiSNA Universidad Pública de Navarra (UPNA) Pamplona Spain
- Laboratorio de Ciencias de la Actividad Física, el Deporte y la Salud Universidad de Santiago de Chile, USACH Santiago Chile
| | - Mikel Izquierdo
- Navarrabiomed Complejo Hospitalario de Navarra (CHN) IdiSNA Universidad Pública de Navarra (UPNA) Pamplona Spain
- Grupo GICAEDS. Programa de Cultura Física Deporte y Recreación Universidad Santo Tomás Bogotá Colombia
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Abstract
Exercise is a well-known non-pharmacologic agent used to prevent and treat a wide range of pathologic conditions such as metabolic and cardiovascular disease. In this sense, the classic field of exercise physiology has determined the main theoretical and practical bases of physiologic adaptations in response to exercise. However, the last decades were marked by significant advances in analytical laboratory techniques, where the field of biochemistry, genetics and molecular biology promoted exercise science to enter a new era. Regardless of its application, whether in the field of disease prevention or performance, the association of molecular biology with exercise physiology has been fundamental for unveiling knowledge of the molecular mechanisms related to the adaptation to exercise. This chapter will address the natural evolution of exercise physiology toward genetics and molecular biology, emphasizing the collection of integrated analytical approaches that composes the OMICS and their contribution to the field of molecular exercise physiology.
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27
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Ross LM, Slentz CA, Kraus WE. Evaluating Individual Level Responses to Exercise for Health Outcomes in Overweight or Obese Adults. Front Physiol 2019; 10:1401. [PMID: 31798463 PMCID: PMC6867965 DOI: 10.3389/fphys.2019.01401] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 10/30/2019] [Indexed: 11/13/2022] Open
Abstract
Background Understanding group responses to a given exercise exposure is becoming better developed; however, understanding of individual responses to specific exercise exposures is significantly underdeveloped and must advance before personalized exercise medicine can become a functional reality. Herein, utilizing data from the STRRIDE studies, we address some of the key issues surrounding our efforts to develop better understanding of individual exercise responsiveness. Methods We assessed individual cardiometabolic and cardiorespiratory fitness responses in subjects successfully completing STRRIDE I (n = 227) and STRRIDE II (n = 155). Subjects were previously sedentary, overweight or obese men and women with mild-to-moderate dyslipidemia. Subjects were randomized to either an inactive control group or to an exercise training program. Training groups varied to test the differential effects of exercise amount, intensity, and mode on cardiometabolic health outcomes. Measures included fasting plasma glucose, insulin, and lipids; blood pressure, minimal waist circumference, visceral adipose tissue, and peak VO2. Absolute change scores were calculated for each subject as post-intervention minus pre-intervention values in order to evaluate the heterogeneity of health factor responsiveness to exercise training. Results For subjects completing one of the aerobic training programs, change in peak VO2 ranged from a loss of 37% to a gain of 77%. When ranked by magnitude of change, we observed discordant responses among changes in peak VO2 with changes in visceral adipose tissue, HDL-C, triglycerides, and fasting plasma insulin. There was also not a clear, direct relationship observed between magnitudes of individual response in the aforementioned variables with aerobic training adherence levels. This same pattern of highly variable and discordant responses was displayed even when considering subjects with adherence levels greater than 70%. Conclusion Our findings illustrate the unclear relationship between magnitude of individual response for a given outcome with training adherence and specific exercise exposure. These discordant and heterogeneous responses highlight the difficult nature of developing understanding for how individuals will respond to any given exposure. Further investigation into the biological, physiological, and genetics factors affecting individual responsiveness is vital to making personalized exercise medicine a reality.
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Affiliation(s)
- Leanna M Ross
- Duke University Medical Center, Duke Molecular Physiology Institute, Durham, NC, United States
| | - Cris A Slentz
- Duke University Medical Center, Duke Molecular Physiology Institute, Durham, NC, United States.,Division of Cardiology, School of Medicine, Duke University, Durham, NC, United States
| | - William E Kraus
- Duke University Medical Center, Duke Molecular Physiology Institute, Durham, NC, United States.,Division of Cardiology, School of Medicine, Duke University, Durham, NC, United States.,Urbaniak Sports Sciences Institute, School of Medicine, Duke University, Durham, NC, United States
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28
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Caru M, Petrykey K, Drouin S, Beaulieu P, St-Onge P, Lemay V, Bertout L, Laverdiere C, Andelfinger G, Krajinovic M, Sinnett D, Curnier D. Identification of genetic association between cardiorespiratory fitness and the trainability genes in childhood acute lymphoblastic leukemia survivors. BMC Cancer 2019; 19:443. [PMID: 31088516 PMCID: PMC6515640 DOI: 10.1186/s12885-019-5651-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 04/29/2019] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND The progress of treatments of childhood acute lymphoblastic leukemia (ALL) has made it possible to reach a survival rate superior to 80%. However, the treatments lead to several long-term adverse effects, including cardiac toxicity. Although studies have reported associations between genetic variants and cardiorespiratory fitness, none has been performed on childhood ALL survivors. METHODS We performed whole-exome sequencing in 239 childhood ALL survivors from the PETALE cohort. Germline variants (both common and rare) in selected set of genes (N = 238) were analyzed for an association with cardiorespiratory fitness. RESULTS Our results showed that the common variant in the TTN gene was significantly associated with a low cardiorespiratory fitness level (p = 0.0005) and that the LEPR, IGFBPI and ENO3 genes were significantly associated with a low cardiorespiratory fitness level in female survivors (p ≤ 0.002). Also, we detected an association between the low cardiorespiratory fitness level in participants that were stratified to the "high risk" prognostic group and functionally predicted rare variants in the SLC22A16 gene (p = 0.001). Positive associations between cardiorespiratory fitness level and trainability genes were mainly observed in females. CONCLUSIONS For the first time, we observed that low cardiorespiratory fitness in childhood ALL survivors can be associated with variants in genes related to subjects' trainability. These findings could allow better childhood ALL patient follow-up tailored to their genetic profile and cardiorespiratory fitness, which could help reduce at least some of the burden of long-term adverse effects of treatments.
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Affiliation(s)
- Maxime Caru
- Laboratoire de Physiopathologie de l'EXercice (LPEX), École de Kinésiologie et des Sciences de l'Activité physique, Faculté de Médecine, Université de Montréal, CEPSUM, 2100, boulevard Édouard Montpetit, Montréal, QC, H3C 3J7, Canada. .,Department of psychology, Laboratoire EA 4430 - Clinique Psychanalyse Developpement (CliPsyD), University of Paris Nanterre, Nanterre, Ile-de-France, France. .,Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada.
| | - Kateryna Petrykey
- Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada.,Department of pharmacology and physiology, University of Montreal, Montreal, Quebec, Canada
| | - Simon Drouin
- Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada
| | - Patrick Beaulieu
- Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada
| | - Pascal St-Onge
- Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada
| | - Valérie Lemay
- Laboratoire de Physiopathologie de l'EXercice (LPEX), École de Kinésiologie et des Sciences de l'Activité physique, Faculté de Médecine, Université de Montréal, CEPSUM, 2100, boulevard Édouard Montpetit, Montréal, QC, H3C 3J7, Canada.,Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada
| | - Laurence Bertout
- Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada
| | - Caroline Laverdiere
- Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada.,Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
| | - Gregor Andelfinger
- Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada.,Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
| | - Maja Krajinovic
- Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada.,Department of pharmacology and physiology, University of Montreal, Montreal, Quebec, Canada.,Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
| | - Daniel Sinnett
- Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada.,Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
| | - Daniel Curnier
- Laboratoire de Physiopathologie de l'EXercice (LPEX), École de Kinésiologie et des Sciences de l'Activité physique, Faculté de Médecine, Université de Montréal, CEPSUM, 2100, boulevard Édouard Montpetit, Montréal, QC, H3C 3J7, Canada.,Research Center, Sainte-Justine University Health Center, Montreal, Quebec, Canada
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Waller K, Vähä-Ypyä H, Törmäkangas T, Hautasaari P, Lindgren N, Iso-Markku P, Heikkilä K, Rinne J, Kaprio J, Sievänen H, Kujala UM. Long-term leisure-time physical activity and other health habits as predictors of objectively monitored late-life physical activity - A 40-year twin study. Sci Rep 2018; 8:9400. [PMID: 29925959 PMCID: PMC6010475 DOI: 10.1038/s41598-018-27704-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Accepted: 06/07/2018] [Indexed: 02/05/2023] Open
Abstract
Moderate-to-vigorous physical activity (MVPA) in old age is an important indicator of good health and functional capacity enabling independent living. In our prospective twin cohort study with 616 individuals we investigated whether long-term physical activity assessed three times, in 1975, 1982 and 1990 (mean age 48 years in 1990), and other self-reported health habits predict objectively measured MVPA measured with a hip-worn triaxial accelerometer (at least 10 hours per day for at least 4 days) 25 years later (mean age of 73 years). Low leisure-time physical activity at younger age, higher relative weight, smoking, low socioeconomic status, and health problems predicted low MVPA in old age in individual-based analyses (altogether explaining 20.3% of the variation in MVPA). However, quantitative trait modeling indicated that shared genetic factors explained 82% of the correlation between baseline and follow-up physical activity. Pairwise analyses within monozygotic twin pairs showed that only baseline smoking was a statistically significant predictor of later-life MVPA. The results imply that younger-age physical activity is associated with later-life MVPA, but shared genetic factors underlies this association. Of the other predictors mid-life smoking predicted less physical activity at older age independent of genetic factors.
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Affiliation(s)
- Katja Waller
- Faculty of Sport and Health Sciences, University of Jyväskylä, FI-40014, Jyväskylä, Finland
| | - Henri Vähä-Ypyä
- The UKK Institute for Health Promotion Research, FI-33500, Tampere, Finland
| | - Timo Törmäkangas
- Faculty of Sport and Health Sciences, University of Jyväskylä, FI-40014, Jyväskylä, Finland
| | - Pekka Hautasaari
- Faculty of Sport and Health Sciences, University of Jyväskylä, FI-40014, Jyväskylä, Finland
| | - Noora Lindgren
- Turku PET Centre, University of Turku, FI-20014, Turku, Finland
| | - Paula Iso-Markku
- Department of Clinical Physiology and Nuclear Medicine, HUS Medical Imaging Center, Helsinki University Central Hospital and University of Helsinki, FI-00014, Helsinki, Finland
| | - Kauko Heikkilä
- Institute for Molecular Medicine Finland, University of Helsinki, FI-00014, Helsinki, Finland
| | - Juha Rinne
- Turku PET Centre, University of Turku, FI-20014, Turku, Finland
- Clinical Neurology, University of Turku, FI-20014, Turku, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, FI-00014, Helsinki, Finland
- Department of Public Health, University of Helsinki, FI-00014, Helsinki, Finland
| | - Harri Sievänen
- The UKK Institute for Health Promotion Research, FI-33500, Tampere, Finland
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, FI-40014, Jyväskylä, Finland.
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30
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Liu X, Huang G, Niu Z, Wei Y, Wang R. Habitual aerobic exercise, gene APOA5 named rs662799 SNP and response of blood lipid and lipoprotein phenotypes among older Chinese adult. Exp Gerontol 2018; 110:46-53. [PMID: 29758349 DOI: 10.1016/j.exger.2018.05.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 04/27/2018] [Accepted: 05/10/2018] [Indexed: 10/16/2022]
Abstract
BACKGROUND The genetic component of dyslipidemia has been studied in adults but little in older population. It is remains unknown regarding influence and interaction of APOA5 gene single nucleotide polymorphism (SNP) and habitual aerobic exercise (HAE) on changes of blood lipids and lipoprotein phenotypes in older Chinese adults. METHODS Four-hundred-twenty-three old Chinese individuals with HAE were divided into hyperlipidemia and normal groups. We genotyped polymorphic loci using matrix assisted laser desorption ionization time of flight mass spectrometry detection technology (MALDI-TOF). HAE level was assessed by International Physical Activity Questionnaire (IPAQ) scale. RESULTS For three genotypes of rs662799 site, the AG + GG gene carriers presented higher risk of hyperlipidemia compared to the AA carriers, with the ratio of 1.676 (P = .018, 95% CI: 1.092-2.571) for the AG and 1.812 (P = .002, 95% CI: 1.247-2.632) for the GG, respectively. The rs662799 G allele was significantly associated with lower HDL-C but higher TG levels. In relation to different HAE levels, less interaction was observed between the AA carriers and different HAE levels on corresponding lipids changes. The AG + GG carriers with higher HAE levels had significantly lower TG responses compared to those with lower HAE levels (1.45 ± 0.74 mmol/L vs. 1.86 ± 1.15 mmol/L). CONCLUSIONS Excess risk for low HDL-C and hyperlipidemia was associated with rs662799 genotype alleles of APOA5 SNPs in older Chinese adults. Interaction of gene-HAE and HAE levels may induce different responses of blood lipids and lipoprotein phenotypes. HAE levels have less influence on TG changes in the AA carriers; however, high HAE levels appeared to greatly impact TG responses in the AG + GG carriers.
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Affiliation(s)
- Xiangyun Liu
- Key Laboratory of Exercise and Health Sciences of Ministry of Education at the Shanghai University of Sport, 188 Hengren Road, Shanghai 200438, China
| | - Guoyuan Huang
- Pott College of Science, Engineering & Education, University of Southern Indiana, Evansville, USA
| | - Zhanbin Niu
- Key Laboratory of Exercise and Health Sciences of Ministry of Education at the Shanghai University of Sport, 188 Hengren Road, Shanghai 200438, China
| | - Yuqin Wei
- Key Laboratory of Exercise and Health Sciences of Ministry of Education at the Shanghai University of Sport, 188 Hengren Road, Shanghai 200438, China
| | - Ru Wang
- Key Laboratory of Exercise and Health Sciences of Ministry of Education at the Shanghai University of Sport, 188 Hengren Road, Shanghai 200438, China.
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31
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LaMonte MJ. Physical Activity and Heart Failure: Taking Steps to Control a Major Public Health Burden. Am J Lifestyle Med 2018; 14:555-570. [PMID: 33110401 DOI: 10.1177/1559827618769609] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Revised: 03/16/2018] [Accepted: 03/19/2018] [Indexed: 12/24/2022] Open
Abstract
Heart failure (HF) is a complex clinical syndrome that is increasingly prevalent among US adults and accounts for substantial burden of healthcare costs and morbidity. HF is commonly associated with prior myocardial infarction as well as prolonged exposure to hypertension, diabetes, and coronary atherosclerosis. Exercise training is becoming established in the management of HF because of its beneficial effect on both central (cardiac) and peripheral (skeletal muscle) HF mechanisms. The role of habitual physical activity in the primary prevention of HF is less clear. Recent prospective observational studies suggest there is lower risk of developing HF in adults who are more physically activity and have higher cardiorespiratory fitness compared with their less active and fit peers. This article reviews the published evidence on physical activity and HF prevention, discusses potential mechanisms for this benefit, and suggests areas where further research is needed to establish recommendations on the type, amount, and intensity of physical activity required to prevent occurrence of HF.
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Affiliation(s)
- Michael J LaMonte
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo-SUNY, Buffalo, New York
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A meta-analysis of the association of CKM gene rs8111989 polymorphism with sport performance. Biol Sport 2018; 34:323-330. [PMID: 29472734 PMCID: PMC5819473 DOI: 10.5114/biolsport.2017.69819] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2016] [Revised: 01/13/2017] [Accepted: 04/12/2017] [Indexed: 02/07/2023] Open
Abstract
The muscle-specific creatine kinase (CKM) A/G variants (rs8111989) have been associated with skeletal muscle performance in humans; they are correlated with physical performance and contribute to differences in the maximum oxygen uptake (VO2max) responses during power or endurance training. However, there is not enough definitive evidence to demonstrate whether the A and G allelic variants of the CKM gene rs8111989 are indeed genetic factors that can influence human physical performance. In our study, we identified 9 articles on CKM in a literature search, and conducted two meta-analyses on the CKM rs8111989 A/G allele or genotype differences between power or endurance athletes and general controls. We found that the power athletes had a significantly higher frequency of the G allele (OR, 1.14; 95% CI, 1.02-1.28, P=0.03) and GG genotype (OR, 1.54; 95% CI, 1.24-1.91, P<0.0001) compared to controls, but there was no significant difference for the endurance athletes (G allele, OR, 0.95, 95%CI, 0.85-1.06, P=0.34; GG genotype, OR, 1.00, 95%CI, 0.78-1.27, P=1.00). The results provide additional evidence to support the notion that human physical performance might be influenced by genetic profiles, especially in power sports.
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Miarka B, Brito CJ, Fukuda DH, Barros CC, Goulart C, Dal Bello F, Del Vecchio FB. Influence of ACTN3 R/X gene polymorphisms on racing strategy in rowing athletes. INT J PERF ANAL SPOR 2017. [DOI: 10.1080/24748668.2017.1416527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Bianca Miarka
- Department of Physical Education, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Ciro José Brito
- Department of Physical Education, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - David H. Fukuda
- Institute of Exercise Physiology and Wellness, University Central Florida, Orlando, FL, USA
| | | | - Cássia Goulart
- School Nutrition, Federal University of Pelotas, Pelotas, Brazil
| | - Fábio Dal Bello
- Head of Physical Activity and Sports Science Master Program. Universidad Santo Tomás, Santiago, Chile
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Eynon N, Voisin S, Lucia A, Wang G, Pitsiladis Y. Preface: genomics and biology of exercise is undergoing a paradigm shift. BMC Genomics 2017; 18:825. [PMID: 29143593 PMCID: PMC5688488 DOI: 10.1186/s12864-017-4184-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
- Nir Eynon
- Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, Melbourne, VIC, Australia. .,Murdoch Childrens Research Institute, Royal Children's Hospital, Melbourne, Australia.
| | - Sarah Voisin
- Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, Melbourne, VIC, Australia
| | - Alejandro Lucia
- Universidad Europea de Madrid and Research Institute Hospital 12 de octubre, 28670 Villaviciosa de Odón, Madrid, Spain
| | - Guan Wang
- Centre of Sports Medicine for Anti-Doping Research, University of Brighton, Eastbourne, UK
| | - Yannis Pitsiladis
- Centre of Sports Medicine for Anti-Doping Research, University of Brighton, Eastbourne, UK
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LaMonte MJ, Lewis CE, Buchner DM, Evenson KR, Rillamas-Sun E, Di C, Lee IM, Bellettiere J, Stefanick ML, Eaton CB, Howard BV, Bird C, LaCroix AZ. Both Light Intensity and Moderate-to-Vigorous Physical Activity Measured by Accelerometry Are Favorably Associated With Cardiometabolic Risk Factors in Older Women: The Objective Physical Activity and Cardiovascular Health (OPACH) Study. J Am Heart Assoc 2017; 6:e007064. [PMID: 29042429 PMCID: PMC5721888 DOI: 10.1161/jaha.117.007064] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Accepted: 08/04/2017] [Indexed: 12/11/2022]
Abstract
BACKGROUND The relationship between light intensity physical activity (PA), which is common in older adults, and cardiovascular disease (CVD) risk factors is unclear. This study examined associations of accelerometer-measured PA intensity with CVD risk factors in older women of different race-ethnicities. METHODS AND RESULTS Cross-sectional analyses were conducted in 4832 women (mean age 78.9 years; 52.5% white, 30.5% black, 17.1% Hispanic) who were without known CVD and wore triaxial accelerometers a minimum of 4 of 7 days with ≥10 hours/d awake wear-time. Vector magnitude counts per 15-s epoch were used to define time spent in low light (19-225 counts/15 s), high light (226-518), and moderate-to-vigorous; ≥519) intensity PA. Fasting CVD biomarkers, resting blood pressure, waist girth, body mass index, and 10-year predicted CVD risk (Reynolds Risk Score) were measured. After adjusting for age, wear time, race-ethnicity, and potential confounders, each PA measure was favorably associated with mean high-density lipoprotein, triglyceride, glucose, C-reactive protein, body mass index, waist girth, and Reynolds Risk Score (P<0.05, all). Associations with mean blood pressure, insulin, and total and low-density lipoprotein cholesterol were variable. A 30-minute/d increment in PA was associated, on average, with odds ratios for high predicted CVD risk (Reynolds Risk Score ≥20) of 0.96 (95% confidence interval, 0.92, 1.00), 0.88 (0.83, 0.94), and 0.85 (0.79, 0.91) for low light, high light, and moderate-to-vigorous, respectively, and remained significant with further mutual control for PA intensity. CONCLUSIONS PA measured by accelerometry, including light intensity PA, was associated with lower CVD risk factor levels in race-ethnically diverse older women.
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Affiliation(s)
- Michael J LaMonte
- School of Public Health and Health Professions University at Buffalo-SUNY, Buffalo, NY
| | - Cora E Lewis
- School of Medicine, University of Alabama-Birmingham, AL
| | | | - Kelly R Evenson
- Gillings School of Public Health, University of North Carolina, Chapel Hill, NC
| | | | - Chongzhi Di
- Fred Hutchinson Cancer Research Center, Seattle, WA
| | - I-Min Lee
- School of Medicine, Harvard University, Boston, MA
| | | | | | - Charles B Eaton
- Warren Alpert Medical School, Brown University, Providence, RI
| | - Barbara V Howard
- MedStar Health Research Institute and Georgetown/Howard Universities Centers for Clinical and Translational Research, Washington, DC
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Letter to the editor: A genetic-based algorithm for personalized resistance training. Biol Sport 2016; 34:31-33. [PMID: 28416894 PMCID: PMC5377557 DOI: 10.5114/biolsport.2017.63385] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 09/04/2016] [Indexed: 12/18/2022] Open
Abstract
In a recent paper entitled “A genetic-based algorithm for personalized resistance training”, Jones et al. [1] presented an algorithm of 15 performance-associated gene polymorphisms that they propose can determine an athlete’s training response by predicting power and endurance potential. However, from the design of their studies and the data provided, there is no evidence to support these authors’ assertions. Progress towards such a significant development in the field of sport and exercise genomics will require a paradigm shift in line with recent recommendations for international collaborations such as the Athlome Project (see www.athlomeconsortium.org). Large-scale initiatives, involving numerous multi-centre and well-phenotyped exercise training and elite performance cohorts, will be necessary before attempting to derive and replicate training and/or performance algorithms.
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