Genetic predisposition score predicts the increases of knee strength and muscle mass after one-year exercise in healthy elderly

The Genetic Association with Athlete Status, Physical Performance, and Injury Risk in Soccer

The aim of this review was to critically appraise the literature concerning the genetic association with athlete status, physical performance, and injury risk in soccer. The objectives were to provide guidance on which genetic markers could potentially be used as part of future practice in soccer and to provide direction for future research in this area. The most compelling evidence identified six genetic polymorphisms to be associated with soccer athlete status (ACE I/D; ACTN3 rs1815739; AGT rs699; MCT1 rs1049434; NOS3 rs2070744; PPARA rs4253778), six with physical performance (ACTN3 rs1815739; AMPD1 rs17602729; BDNF rs6265; COL2A1 rs2070739; COL5A1 rs12722; NOS3 rs2070744), and seven with injury risk (ACTN3 rs1815739; CCL2 rs2857656; COL1A1 rs1800012; COL5A1 rs12722; EMILIN1 rs2289360; IL6 rs1800795; MMP3 rs679620). As well as replication by independent groups, large-scale genome-wide association studies are required to identify new genetic markers. Future research should also investigate the physiological mechanisms associating these polymorphisms with specific phenotypes. Further, researchers should investigate the above associations in female and non-Caucasian soccer players, as almost all published studies have recruited male participants of European ancestry. Only after robust, independently replicated genetic data have been generated, can genetic testing be considered an additional tool to potentially inform future practice in soccer.

Evidence of whole-body vibration exercises on body composition changes in older individuals: a systematic review and meta-analysis

Introduction: The aging process is associated with changes in body composition, including fat gain and skeletal muscle loss from middle age onward. Moreover, increased risk of functional decline and the development of chronic diseases are also related to aging. Objective: This systematic review and meta-analysis aimed to evaluate the effects of whole-body vibration exercise (WBVE), as a physical exercise, on body composition in people over 60 years of age. Methods: Searches were performed on PubMed, Scopus, Web of Science, and Embase. Only randomized clinical trials evaluating the effects of WBVE on body composition in older individuals were considered. The methodological quality of the studies involved was assessed using the Physiotherapy Evidence Database (PEDro) scale, recommendations from the Cochrane Collaboration were used to assess risk of bias, and quality of evidence was assessed using the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) methodology. RevMan 5.4 was used to calculate standardized mean differences and confidence intervals of 95% (CIs). Results: Eight studies were included in this review with a mean methodological quality score of 7.5, which is considered high quality on the PEDro scale. The included studies suggest that more robust research with protocols and well-designed comparison groups is required to better assess changes in the body composition of older individuals through WBVE. Quantitative results were calculated, with differences in weighted means, differences in standardized means, and 95% confidence intervals (CIs). Conclusion: WBVE evaluated by the studies included in this review did not demonstrate improvements in body composition, and no significant effect of WBVE was found on fat mass with standardized differences (SD = -1.92; 95% CI: -4.81 to -0.98; p = 0.19), lean mass with standardized mean differences (SMD = 0.06 CI 95% [-0.21; -0.33]; p = 0.67), or skeletal muscle mass with standardized differences (SD = 0.10; CI 95% [-1.62; 1.83]; p = 0.91). Therefore, to date, there is lack of adequate evidence to state that WBVE can benefit the body composition of men and women over 60 years of age. However, further studies are required to better understand the physiological impacts of WBVE on body composition. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/#myprosperoCRD42021248871, identifier CRD42021248871.

Genetic polymorphisms of muscular fitness in young healthy men

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.

Polygenic Models Partially Predict Muscle Size and Strength but Not Low Muscle Mass in Older Women

Background: Heritability explains 45-82% of muscle mass and strength variation, yet polygenic models for muscle phenotypes in older women are scarce. Therefore, the objective of the present study was to (1) assess if total genotype predisposition score (GPSTOTAL) for a set of polymorphisms differed between older women with low and high muscle mass, and (2) utilise a data-driven GPS (GPSDD) to predict the variance in muscle size and strength-related phenotypes. Methods: In three-hundred 60- to 91-year-old Caucasian women (70.7 ± 5.7 years), skeletal muscle mass, biceps brachii thickness, vastus lateralis anatomical cross-sectional area (VLACSA), hand grip strength (HGS), and elbow flexion (MVCEF) and knee extension (MVCKE) maximum voluntary contraction were measured. Participants were classified as having low muscle mass if the skeletal muscle index (SMI) < 6.76 kg/m2 or relative skeletal muscle mass (%SMMr) < 22.1%. Genotyping was completed for 24 single-nucleotide polymorphisms (SNPs). GPSTOTAL was calculated from 23 SNPs and compared between the low and high muscle mass groups. A GPSDD was performed to identify the association of SNPs with other skeletal muscle phenotypes. Results: There was no significant difference in GPSTOTAL between low and high muscle mass groups, irrespective of classification based on SMI or %SMMr. The GPSDD model, using 23 selected SNPs, revealed that 13 SNPs were associated with at least one skeletal muscle phenotype: HIF1A rs11549465 was associated with four phenotypes and, in descending number of phenotype associations, ACE rs4341 with three; PTK2 rs7460 and CNTFR rs2070802 with two; and MTHFR rs17421511, ACVR1B rs10783485, CNTF rs1800169, MTHFR rs1801131, MTHFR rs1537516, TRHR rs7832552, MSTN rs1805086, COL1A1 rs1800012, and FTO rs9939609 with one phenotype. The GPSDD with age included as a predictor variable explained 1.7% variance of biceps brachii thickness, 12.5% of VLACSA, 19.0% of HGS, 8.2% of MVCEF, and 9.6% of MVCKE. Conclusions: In older women, GPSTOTAL did not differ between low and high muscle mass groups. However, GPSDD was associated with muscle size and strength phenotypes. Further advancement of polygenic models to understand skeletal muscle function during ageing might become useful in targeting interventions towards older adults most likely to lose physical independence.

Perspectives in Sports Genomics

Human athletic performance is a complex phenotype influenced by environmental and genetic factors, with most exercise-related traits being polygenic in nature. The aim of this article is to outline some of the challenge faced by sports genetics as this relatively new field moves forward. This review summarizes recent advances in sports science and discusses the impact of the genome, epigenome and other omics (such as proteomics and metabolomics) on athletic performance. The article also highlights the current status of gene doping and examines the possibility of applying genetic knowledge to predict athletes’ injury risk and to prevent the rare but alarming occurrence of sudden deaths during sporting events. Future research in large cohorts of athletes has the potential to detect new genetic variants and to confirm the previously identified DNA variants believed to explain the natural predisposition of some individuals to certain athletic abilities and health benefits. It is hoped that this article will be useful to sports scientists who seek a greater understanding of how genetics influences exercise science and how genomic and other multi-omics approaches might support performance analysis, coaching, personalizing nutrition, rehabilitation and sports medicine, as well as the potential to develop new rationale for future scientific investigation.

Effects of Whole-Body Vibration Training on Body Composition, Cardiometabolic Risk, and Strength in the Population Who Are Overweight and Obese: A Systematic Review With Meta-analysis

OBJECTIVES

To assess the effects of whole-body vibration training (WBVT) on body composition, metabolic and cardiovascular risk variables, and lower limb strength in participants who are overweight/obese.

DATA SOURCES

A systematic review with meta-analysis was conducted in 3 databases (PubMed-MEDLINE, Web of Science, and Cochrane Library) from inception through to January 26, 2020.

STUDY SELECTION

Studies analyzing the effect of WBVT on body composition variables, metabolic profile, blood pressure, heart rate, and lower limb strength in the population who are overweight/obese, with interventions of a minimum length of 2 weeks were included.

DATA EXTRACTION

After applying the inclusion and exclusion criteria, 23 studies involving 884 participants who were obese/overweight (experimental group: 543; weight=79.9 kg; body mass index (BMI) =31.3 kg/m², obesity class I according to World Health Organization) were used in the quantitative analysis. The sex of the participants involved in the studies were as follows: (1) 17 studies included only female participants; (2) 1 study included only boys, and (3) 5 studies included both sexes. Meta-analysis, subgroup analysis, and meta-regression methods were used to calculate the mean difference and standardized mean difference (SMD; ± 95% confidence intervals [CIs]) as well as to analyze the effects of pre-post intervention WBVT and differences from control groups.

DATA SYNTHESIS

WBVT led to a significant decrease in fat mass (-1.07 kg, not clinically significant). In addition, WBVT reduced systolic blood pressure (-7.01 mmHg, clinically significant), diastolic blood pressure (-1.83 mmHg), and heart rate (-2.23 bpm), as well as increased the lower extremity strength (SMD=0.63; range, 0.40-0.86). On the other hand, WBVT did not modify the weight, BMI, muscle mass, cholesterol, triglycerides, or glucose.

CONCLUSIONS

WBVT could be an effective training modality to reduce blood pressure (clinically relevant) and resting heart rate. In addition, WBVT led to improved lower limb strength. However, these findings were not consistent with significant improvements on other variables associated with metabolic syndrome (body composition, cholesterol, triglycerides, glucose).

Symptom Science: Omics and Response to Non-Pharmacological Interventions

Incorporating omics into non-pharmacological intervention research design could provide a better understanding of the variability in response to these interventions. It would also provide evidence for precision-based non-pharmacological interventions, including interventions focused on symptoms. The purpose of this manuscript was to present examples of studies that have used omics to examine response to non-pharmacological intervention. Using the interventions of exercise, diet (related to obesity), cognitive based therapy, and alternative mind-body practices (meditation, yoga, and tai chi), PubMed was searched to identify studies that incorporated genomic or other omic approaches as part of a non-pharmacological intervention. The review identified genes associated with the effectiveness of each of the interventions. Although there were no genes that were associated with all four interventions, there were nine genes that were the focus of more than one intervention (ACE, BDNF, COMT, CXCL8, IL6, SL6A4, TNF, GSTM1, PTGER3). All nine of these genes were either directly or indirectly biologically related to one another, suggesting that this cadre of genes could serve as an initiation point for investigations using omic approaches to better understand response to non-pharmacological interventions.

Associations of combined genetic and epigenetic scores with muscle size and muscle strength: a pilot study in older women

BACKGROUND

Inter-individual variance in skeletal muscle is closely related to genetic architecture and epigenetic regulation. Studies have examined genetic and epigenetic relationships with characteristics of ageing muscle separately, while no study has combined both genetic and epigenetic profiles in ageing muscle research. The aim of this study was to evaluate the association between combined genetic and methylation scores and skeletal muscle phenotypes in older women.

METHODS

Forty-eight older Caucasian women (aged 65-79 years) were included in this study. Biceps brachii thickness and vastus lateralis anatomical cross-sectional area (ACSA_VL ) were measured by ultrasonography. Maximum isometric elbow flexion (MVC_EF ) and knee extension (MVC_KE ) torques were measured by a customized dynamometer. The muscle-driven genetic predisposition score (GPS_SNP ) was calculated based on seven muscle-related single nucleotide polymorphisms (SNPs). DNA methylation levels of whole blood samples were analysed using Infinium MethylationEPIC BeadChip arrays. The DNA methylation score was calculated as a weighted sum of methylation levels of sarcopenia-driven CpG sites (MS_SAR ) or an overall gene-wise methylation score (MS_SNP , the mean methylation level of CpG sites located in muscle-related genes). Linear regression models were built to study genetic and epigenetic associations with muscle size and strength. Three models were built with both genetic and methylation scores: (1) MS_SAR  + GPS_SNP , (2) MS_SNP  + GPS_SNP , and (3) gene-wise combined scores which were calculated as the ratio of the SNP score to the mean methylation level of promoters in the corresponding gene. Additional models with only a genetic or methylation score were also built. All models were adjusted for age and BMI.

RESULTS

MS_SAR was negatively associated with ACSA_VL , MVC_EF , and MVC_KE and explained 10.1%, 35.5%, and 40.1% of the variance, respectively. MS_SAR explained more variance in these muscular phenotypes than GPS_SNP , MS_SNP , and models including both genetic and methylation scores. MS_SNP and GPS_SNP accounted for less than 8% and 5% of the variance in all muscular phenotypes, respectively. The genotype and methylation level of CNTF was positively related to MVC_KE (P = 0.03) and explained 12.2% of the variance. The adjusted R² and Akaike information criterion showed that models with only a MS_SAR performed the best in explaining inter-individual variance in muscular phenotypes.

CONCLUSIONS

Our results improve the understanding of inter-individual variance in muscular characteristics of older women and suggest a possible application of a sarcopenia-driven methylation score to muscle strength estimation in older women while the combination with a genetic score still needs to be further studied.

The Genetic Effect on Muscular Changes in an Older Population: A Follow-Up Study after One-Year Cessation of Structured Training

Older adults lose muscle mass and strength at different speeds after the cessation of physical exercise, which might be genotype related. This study aimed to explore the genetic association with changes in muscle mass and strength one year after the cessation of structured training in an older population. Participants (n = 113, aged between 61 and 81 years) who performed one-year of combined fitness (n = 44) or whole-body vibration (n = 69) training were assessed one year after the cessation of the training. Whole-body skeletal muscle mass and knee strength were measured. Data-driven genetic predisposition scores (GPSs) were calculated and analysed in a general linear model with sex, age, body mass index and post-training values of skeletal muscle mass or muscle strength as covariates. Forty-six single nucleotide polymorphisms (SNPs) from an initial 170 muscle-related SNPs were identified as being significantly linked to muscular changes after cessation. Data-driven GPSs and over time muscular changes were significantly related (p < 0.01). Participants with higher GPSs had less muscular declines during the cessation period while data-driven GPSs accounted for 26–37% of the phenotypic variances. Our findings indicate that the loss of training benefits in older adults is partially genotype related.

The Prospective Study of Epigenetic Regulatory Profiles in Sport and Exercise Monitored Through Chromosome Conformation Signatures

The integration of genetic and environmental factors that regulate the gene expression patterns associated with exercise adaptation is mediated by epigenetic mechanisms. The organisation of the human genome within three-dimensional space, known as chromosome conformation, has recently been shown as a dynamic epigenetic regulator of gene expression, facilitating the interaction of distal genomic regions due to tight and regulated packaging of chromosomes in the cell nucleus. Technological advances in the study of chromosome conformation mean a new class of biomarker-the chromosome conformation signature (CCS)-can identify chromosomal interactions across several genomic loci as a collective marker of an epigenomic state. Investigative use of CCSs in biological and medical research shows promise in identifying the likelihood that a disease state is present or absent, as well as an ability to prospectively stratify individuals according to their likely response to medical intervention. The association of CCSs with gene expression patterns suggests that there are likely to be CCSs that respond, or regulate the response, to exercise and related stimuli. The present review provides a contextual background to CCS research and a theoretical framework discussing the potential uses of this novel epigenomic biomarker within sport and exercise science and medicine.

Differentially methylated gene patterns between age-matched sarcopenic and non-sarcopenic women

BACKGROUND

Sarcopenia is characterized by progressive decreases in muscle mass, muscle strength, and muscle function with ageing. Although many studies have investigated the mechanisms of sarcopenia, its connection with epigenetic factors, such as DNA methylation, still remains poorly understood. The aim of this study was to explore sarcopenia-related DNA methylation differences in blood samples between age-matched sarcopenic and non-sarcopenic older women.

METHODS

A sarcopenic group (n = 24) was identified and selected from a set of 247 older Caucasian women (aged 65-80 years) based on cut-off points of skeletal muscle index at 6.75 kg/m² and grip strength at 26 kg (the lower quintile of grip strength in the set). A non-sarcopenic group (n = 24) was created with a similar age distribution as that of the sarcopenic group. DNA methylation patterns of whole blood samples from both groups were analysed using Infinium MethylationEPIC BeadChip arrays. Differentially methylated cytosin-phosphate-guanine sites (dmCpGs) were identified at a P value threshold of 0.01 by comparing methylation levels between the sarcopenic and non-sarcopenic groups at each CpG site. dmCpG-related genes were annotated based on Homo sapiens hg19 genome build. The functions of these genes were further examined by GO and KEGG pathway enrichment analysis.

RESULTS

The global methylation level of all analysed CpG sites (n = 788 074) showed no significant difference between the sarcopenic and non-sarcopenic groups (0.812), while the average methylation level of dmCpGs (n = 6258) was significantly lower in the sarcopenic group (0.004). The sarcopenic group had significantly higher methylation levels in TSS200 (the region from transcription start site to 200 nucleotides upstream of the site) and lower methylation levels in gene body and 3'UTR regions. In respect of CpG regions, CpG islands in promoters and some intragenic regions showed greater levels of methylation in the sarcopenic group. dmCpG-related KEGG pathways were mainly associated with muscle function, actin cytoskeleton regulation, and energy metabolism. Seven genes (HSPB1, PBX4, CNKSR3, ORMDL3, MIR10A, ZNF619, and CRADD) were found with the same methylation direction as previous studies of blood sample methylation during ageing. Fifty-four genes were shared with previous studies of resistance training.

CONCLUSIONS

Our results improve understanding of epigenetic mechanisms of sarcopenia by identifying sarcopenia-related DNA methylation differences in blood samples of older women. These methylation differences suggest underlying alterations of gene expression and pathway function, which can partially explain sarcopenia-related muscular changes.