Dataset Information

No Evidence of a Common DNA Variant Profile Specific to World Class Endurance Athletes.

ABSTRACT: There are strong genetic components to cardiorespiratory fitness and its response to exercise training. It would be useful to understand the differences in the genomic profile of highly trained endurance athletes of world class caliber and sedentary controls. An international consortium (GAMES) was established in order to compare elite endurance athletes and ethnicity-matched controls in a case-control study design. Genome-wide association studies were undertaken on two cohorts of elite endurance athletes and controls (GENATHLETE and Japanese endurance runners), from which a panel of 45 promising markers was identified. These markers were tested for replication in seven additional cohorts of endurance athletes and controls: from Australia, Ethiopia, Japan, Kenya, Poland, Russia and Spain. The study is based on a total of 1520 endurance athletes (835 who took part in endurance events in World Championships and/or Olympic Games) and 2760 controls. We hypothesized that world-class athletes are likely to be characterized by an even higher concentration of endurance performance alleles and we performed separate analyses on this subsample. The meta-analysis of all available studies revealed one statistically significant marker (rs558129 at GALNTL6 locus, p = 0.0002), even after correcting for multiple testing. As shown by the low heterogeneity index (I2 = 0), all eight cohorts showed the same direction of association with rs558129, even though p-values varied across the individual studies. In summary, this study did not identify a panel of genomic variants common to these elite endurance athlete groups. Since GAMES was underpowered to identify alleles with small effect sizes, some of the suggestive leads identified should be explored in expanded comparisons of world-class endurance athletes and sedentary controls and in tightly controlled exercise training studies. Such studies have the potential to illuminate the biology not only of world class endurance performance but also of compromised cardiac functions and cardiometabolic diseases.

SUBMITTER: Rankinen T

PROVIDER: S-EPMC4732768 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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No Evidence of a Common DNA Variant Profile Specific to World Class Endurance Athletes.

Rankinen Tuomo T Fuku Noriyuki N Wolfarth Bernd B Wang Guan G Sarzynski Mark A MA Alexeev Dmitry G DG Ahmetov Ildus I II Boulay Marcel R MR Cieszczyk Pawel P Eynon Nir N Filipenko Maxim L ML Garton Fleur C FC Generozov Edward V EV Govorun Vadim M VM Houweling Peter J PJ Kawahara Takashi T Kostryukova Elena S ES Kulemin Nickolay A NA Larin Andrey K AK Maciejewska-Karłowska Agnieszka A Miyachi Motohiko M Muniesa Carlos A CA Murakami Haruka H Ospanova Elena A EA Padmanabhan Sandosh S Pavlenko Alexander V AV Pyankova Olga N ON Santiago Catalina C Sawczuk Marek M Scott Robert A RA Uyba Vladimir V VV Yvert Thomas T Perusse Louis L Ghosh Sujoy S Rauramaa Rainer R North Kathryn N KN Lucia Alejandro A Pitsiladis Yannis Y Bouchard Claude C

PloS one 20160129 1

There are strong genetic components to cardiorespiratory fitness and its response to exercise training. It would be useful to understand the differences in the genomic profile of highly trained endurance athletes of world class caliber and sedentary controls. An international consortium (GAMES) was established in order to compare elite endurance athletes and ethnicity-matched controls in a case-control study design. Genome-wide association studies were undertaken on two cohorts of elite enduranc ...[more]

PMID: 26824906

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Project description:BackgroundCarbohydrate (CHO) and carbohydrate-protein co-ingestion (CHO-P) have been shown to be equally effective for enhancing glycogen resynthesis and subsequent same-day performance when CHO intake is suboptimal (≤0.8 g/kg). Few studies have specifically examined the effect of isocaloric CHO vs CHO-P consumption on subsequent high-intensity aerobic performance with limited time to recover (≤2 hours) in masters class endurance athletes.MethodsThis was a randomized, double-blind between-subject design. Twenty-two male masters class endurance athletes (age 49.1 ± 6.9 years; height 175.8 ± 4.8 cm; body mass 80.7 ± 8.6 kg; body fat (%) 19.1 ± 5.8; VO2peak 48.6 ± 6.7 ml·kg·min-1) were assigned to consume one of three beverages during a 2-hour recovery period: Placebo (PLA; electrolytes and water), CHO (1.2 g/kg bm), or CHO-P (0.8 g/kg bm CHO + 0.4 g/kg bm PRO). All beverages were standardized to one liter (~32 oz.) of total fluid volume regardless of the treatment group. During Visit #1, participants completed graded exercise testing on a cycle ergometer to determine VO2peak and peak power output (PPO, watts). Visit #2 consisted of familiarization with the high-intensity protocol including 5 × 4 min intervals at 70-80% of PPO with 2 min of active recovery at 50 W, followed by a time to exhaustion (TTE) test at 90% PPO. During Visit#3, the same high-intensity interval protocol with TTE was conducted pre-and post-beverage consumption.ResultsA one-way ANCOVA indicated a significant difference among the group means for the posttest TTE (F2,18 = 6.702, p = .007, ƞ2 = .427) values after adjusting for the pretest differences. TTE performance in the second exercise bout improved for the CHO (295.48 ± 24.90) and CHO-P (255.08 ± 25.07 sec) groups. The water and electrolyte solution was not effective in restoring TTE performance in the PLA group (171.13 ± 23.71 sec).ConclusionsBoth CHO and CHO-P effectively promoted an increase in TTE performance with limited time to recover in this sample of masters class endurance athletes. Water and electrolytes alone were not effective for restoring endurance capacity during the second bout of exhaustive exercise.

Project description:BackgroundThe ataxia-telangiectasia mutated (ATM) kinase phosphorylates and activates several downstream targets that are essential for DNA damage repair, cell cycle inhibition and apoptosis. Germline biallelic inactivation of the ATM gene causes ataxia-telangiectasia (A-T), and heterozygous pathogenic variant (PV) carriers are at increased risk of cancer, notably breast cancer. This study aimed to investigate whether DNA methylation profiling can be useful as a biomarker to identify tumors arising in ATM PV carriers, which may help for the management and optimal tailoring of therapies of these patients.MethodsBreast tumor enriched DNA was prepared from 2 A-T patients, 27 patients carrying an ATM PV, 6 patients carrying a variant of uncertain clinical significance and 484 noncarriers enrolled in epidemiological studies conducted in France and Australia to investigate genetic and nongenetic factors involved in breast cancer susceptibility. Genome-wide DNA methylation analysis was performed using the Illumina Infinium HumanMethylation EPIC and 450K BeadChips. Correlation between promoter methylation and gene expression was assessed for 10 tumors for which transcriptomic data were available.ResultsWe found that the ATM promoter was hypermethylated in 62% of tumors of heterozygous PV carriers compared to the mean methylation level of ATM promoter in tumors of noncarriers. Gene set enrichment analyses identified 47 biological pathways enriched in hypermethylated genes involved in neoplastic, neurodegenerative and metabolic-related pathways in tumor of PV carriers. Among the 327 differentially methylated promoters, promoters of ARHGAP40, SCGB3A1 (HIN-1), and CYBRD1 (DCYTB) were hypermethylated and associated with a lower gene expression in these tumors. Moreover, using three different deep learning algorithms (logistic regression, random forest and XGBoost), we identified a set of 27 additional biomarkers predictive of ATM status, which could be used in the future to provide evidence for or against pathogenicity in ATM variant classification strategies.ConclusionsWe showed that breast tumors that arise in women who carry an ATM PV display a specific genome-wide DNA methylation profile. Specifically, the methylation pattern of 27 key gene promoters was predictive of ATM PV status of the women. These genes may also represent new medical prevention and therapeutic targets for these women.

Project description:Background: Properly performed training is a matter of importance for endurance athletes (EA). It allows for achieving better results and safer participation. Recently, the development of machine learning methods has been observed in sports diagnostics. Velocity at anaerobic threshold (VAT), respiratory compensation point (VRCP), and maximal velocity (Vmax) are the variables closely corresponding to endurance performance. The primary aims of this study were to find the strongest predictors of VAT, VRCP, Vmax, to derive and internally validate prediction models for males (1) and females (2) under TRIPOD guidelines, and to assess their machine learning accuracy. Materials and Methods: A total of 4001 EA (nmales = 3300, nfemales = 671; age = 35.56 ± 8.12 years; BMI = 23.66 ± 2.58 kg·m-2; VO2max = 53.20 ± 7.17 mL·min-1·kg-1) underwent treadmill cardiopulmonary exercise testing (CPET) and bioimpedance body composition analysis. XGBoost was used to select running performance predictors. Multivariable linear regression was applied to build prediction models. Ten-fold cross-validation was incorporated for accuracy evaluation during internal validation. Results: Oxygen uptake, blood lactate, pulmonary ventilation, and somatic parameters (BMI, age, and body fat percentage) showed the highest impact on velocity. For VAT R2 = 0.57 (1) and 0.62 (2), derivation RMSE = 0.909 (1); 0.828 (2), validation RMSE = 0.913 (1); 0.838 (2), derivation MAE = 0.708 (1); 0.657 (2), and validation MAE = 0.710 (1); 0.665 (2). For VRCP R2 = 0.62 (1) and 0.67 (2), derivation RMSE = 1.066 (1) and 0.964 (2), validation RMSE = 1.070 (1) and 0.978 (2), derivation MAE = 0.832 (1) and 0.752 (2), validation MAE = 0.060 (1) and 0.763 (2). For Vmax R2 = 0.57 (1) and 0.65 (2), derivation RMSE = 1.202 (1) and 1.095 (2), validation RMSE = 1.205 (1) and 1.111 (2), derivation MAE = 0.943 (1) and 0.861 (2), and validation MAE = 0.944 (1) and 0.881 (2). Conclusions: The use of machine-learning methods allows for the precise determination of predictors of both submaximal and maximal running performance. Prediction models based on selected variables are characterized by high precision and high repeatability. The results can be used to personalize training and adjust the optimal therapeutic protocol in clinical settings, with a target population of EA.

Dataset Information

No Evidence of a Common DNA Variant Profile Specific to World Class Endurance Athletes.

Publications

No Evidence of a Common DNA Variant Profile Specific to World Class Endurance Athletes.

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