Joint identification of genetic variants for physical activity in Korean population

Genomic predictors of physical activity and athletic performance

Physical activity and athletic performance are complex phenotypes influenced by environmental and genetic factors. Recent advances in lifestyle and behavioral genomics led to the discovery of dozens of DNA polymorphisms (variants) associated with physical activity and allowed to use them as genetic instruments in Mendelian randomization studies for identifying the causal links between physical activity and health outcomes. On the other hand, exercise and sports genomics studies are focused on the search for genetic variants associated with athlete status, sports injuries and individual responses to training and supplement use. In this review, the findings of studies investigating genetic markers and their associations with physical activity and athlete status are reported. As of the end of September 2023, a total of 149 variants have been associated with various physical activity traits (of which 42 variants are genome-wide significant) and 253 variants have been linked to athlete status (115 endurance-related, 96 power-related, and 42 strength-related).

Genetic Determinants of Leisure-Time Physical Activity in the Hungarian General and Roma Populations

Leisure-time physical activity (LTPA) is one of the modifiable lifestyle factors that play an important role in the prevention of non-communicable (especially cardiovascular) diseases. Certain genetic factors predisposing to LTPA have been previously described, but their effects and applicability on different ethnicities are unknown. Our present study aims to investigate the genetic background of LTPA using seven single nucleotide polymorphisms (SNPs) in a sample of 330 individuals from the Hungarian general (HG) and 314 from the Roma population. The LTPA in general and three intensity categories of it (vigorous, moderate, and walking) were examined as binary outcome variables. Allele frequencies were determined, individual correlations of SNPs to LTPA, in general, were determined, and an optimized polygenetic score (oPGS) was created. Our results showed that the allele frequencies of four SNPs differed significantly between the two study groups. The C allele of rs10887741 showed a significant positive correlation with LTPA in general (OR = 1.48, 95% CI: 1.12-1.97; p = 0.006). Three SNPs (rs10887741, rs6022999, and rs7023003) were identified by the process of PGS optimization, whose cumulative effect shows a strong significant positive association with LTPA in general (OR = 1.40, 95% CI: 1.16-1.70; p < 0.001). The oPGS showed a significantly lower value in the Roma population compared with the HG population (oPGS_Roma: 2.19 ± SD: 0.99 vs. oPGS_HG: 2.70 ± SD: 1.06; p < 0.001). In conclusion, the coexistence of genetic factors that encourage leisure-time physical activity shows a more unfavorable picture among Roma, which may indirectly contribute to their poor health status.

Skeletal Muscles of Sedentary and Physically Active Aged People Have Distinctive Genic Extrachromosomal Circular DNA Profiles

To bring new extrachromosomal circular DNA (eccDNA) enrichment technologies closer to the clinic, specifically for screening, early diagnosis, and monitoring of diseases or lifestyle conditions, it is paramount to identify the differential pattern of the genic eccDNA signal between two states. Current studies using short-read sequenced purified eccDNA data are based on absolute numbers of unique eccDNAs per sample or per gene, length distributions, or standard methods for RNA-seq differential analysis. Previous analyses of RNA-seq data found significant transcriptomics difference between sedentary and active life style skeletal muscle (SkM) in young people but very few in old. The first attempt using circulomics data from SkM and blood of aged lifelong sedentary and physically active males found no difference at eccDNA level. To improve the capability of finding differences between circulomics data groups, we designed a computational method to identify Differentially Produced per Gene Circles (DPpGCs) from short-read sequenced purified eccDNA data based on the circular junction, split-read signal, of the eccDNA, and implemented it into a software tool DifCir in Matlab. We employed DifCir to find to the distinctive features of the influence of the physical activity or inactivity in the aged SkM that would have remained undetected by transcriptomics methods. We mapped the data from tissue from SkM and blood from two groups of aged lifelong sedentary and physically active males using Circle_finder and subsequent merging and filtering, to find the number and length distribution of the unique eccDNA. Next, we used DifCir to find up-DPpGCs in the SkM of the sedentary and active groups. We assessed the functional enrichment of the DPpGCs using Disease Gene Network and Gene Set Enrichment Analysis. To find genes that produce eccDNA in a group without comparison with another group, we introduced a method to find Common PpGCs (CPpGCs) and used it to find CPpGCs in the SkM of the sedentary and active group. Finally, we found the eccDNA that carries whole genes. We discovered that the eccDNA in the SkM of the sedentary group is not statistically different from that of physically active aged men in terms of number and length distribution of eccDNA. In contrast, with DifCir we found distinctive gene-associated eccDNA fingerprints. We identified statistically significant up-DPpGCs in the two groups, with the top up-DPpGCs shed by the genes AGBL4, RNF213, DNAH7, MED13, and WWTR1 in the sedentary group, and ZBTB7C, TBCD, ITPR2, and DDX11-AS1 in the active group. The up-DPpGCs in both groups carry mostly gene fragments rather than whole genes. Though the subtle transcriptomics difference, we found RYR1 to be both transcriptionally up-regulated and up-DPpGCs gene in sedentary SkM. DifCir emphasizes the high sensitivity of the circulome compared to the transcriptome to detect the molecular fingerprints of exercise in aged SkM. It allows efficient identification of gene hotspots that excise more eccDNA in a health state or disease compared to a control condition.

Genetic Pathways Underlying Individual Differences in Regular Physical Activity

Twin and family studies show a strong contribution of genetic factors to physical activity (PA) assessed by either self-report or accelerometers. PA heritability is around 43% across the lifespan. Genome-wide association studies have implied biological pathways related to exercise ability and enjoyment. A polygenic score based on genetic variants influencing PA could help improve the success of intervention programs.

Genome-wide association studies of 27 accelerometry-derived physical activity measurements identified novel loci and genetic mechanisms

Physical inactivity (PA) is an important risk factor for a wide range of diseases. Previous genome-wide association studies (GWAS), based on self-reported data or a small number of phenotypes derived from accelerometry, have identified a limited number of genetic loci associated with habitual PA and provided evidence for involvement of central nervous system in mediating genetic effects. In this study, we derived 27 PA phenotypes from wrist accelerometry data obtained from 88,411 UK Biobank study participants. Single-variant association analysis based on mixed-effects models and transcriptome-wide association studies (TWAS) together identified 5 novel loci that were not detected by previous studies of PA, sleep duration and self-reported chronotype. For both novel and previously known loci, we discovered associations with novel phenotypes including active-to-sedentary transition probability, light-intensity PA, activity during different times of the day and proxy phenotypes to sleep and circadian patterns. Follow-up studies including TWAS, colocalization, tissue-specific heritability enrichment, gene-set enrichment and genetic correlation analyses indicated the role of the blood and immune system in modulating the genetic effects and a secondary role of the digestive and endocrine systems. Our findings provided important insights into the genetic architecture of PA and its underlying mechanisms.

Identification of novel and rare variants associated with handgrip strength using whole genome sequence data from the NHLBI Trans-Omics in Precision Medicine (TOPMed) Program

Handgrip strength is a widely used measure of muscle strength and a predictor of a range of morbidities including cardiovascular diseases and all-cause mortality. Previous genome-wide association studies of handgrip strength have focused on common variants primarily in persons of European descent. We aimed to identify rare and ancestry-specific genetic variants associated with handgrip strength by conducting whole-genome sequence association analyses using 13,552 participants from six studies representing diverse population groups from the Trans-Omics in Precision Medicine (TOPMed) Program. By leveraging multiple handgrip strength measures performed in study participants over time, we increased our effective sample size by 7-12%. Single-variant analyses identified ten handgrip strength loci among African-Americans: four rare variants, five low-frequency variants, and one common variant. One significant and four suggestive genes were identified associated with handgrip strength when aggregating rare and functional variants; all associations were ancestry-specific. We additionally leveraged the different ancestries available in the UK Biobank to further explore the ancestry-specific association signals from the single-variant association analyses. In conclusion, our study identified 11 new loci associated with handgrip strength with rare and/or ancestry-specific genetic variations, highlighting the added value of whole-genome sequencing in diverse samples. Several of the associations identified using single-variant or aggregate analyses lie in genes with a function relevant to the brain or muscle or were reported to be associated with muscle or age-related traits. Further studies in samples with sequence data and diverse ancestries are needed to confirm these findings.

Genetic variants related to physical activity or sedentary behaviour: a systematic review

BACKGROUND

Research shows that part of the variation in physical activity and sedentary behaviour may be explained by genetic factors. Identifying genetic variants associated with physical activity and sedentary behaviour can improve causal inference in physical activity research. The aim of this systematic review was to provide an updated overview of the evidence of genetic variants associated with physical activity or sedentary behaviour.

METHODS

We performed systematic literature searches in PubMed and Embase for studies published from 1990 to April 2020 using keywords relating to "physical activity", "exercise", "sedentariness" and "genetics". Physical activity phenotypes were either based on self-report (e.g., questionnaires, diaries) or objective measures (e.g., accelerometry, pedometer). We considered original studies aiming to i) identify new genetic variants associated with physical activity or sedentary behaviour (i.e., genome wide association studies [GWAS]), or ii) assess the association between known genetic variants and physical activity or sedentary behaviour (i.e., candidate gene studies). Study selection, data extraction, and critical appraisal were carried out by independent researchers, and risk of bias and methodological quality was assessed for all included studies.

RESULTS

Fifty-four out of 5420 identified records met the inclusion criteria. Six of the included studies were GWAS, whereas 48 used a candidate gene approach. Only one GWAS and three candidate gene studies were considered high-quality. The six GWAS discovered up to 10 single nucleotide polymorphisms (SNPs) associated with physical activity or sedentariness that reached genome-wide significance. In total, the candidate gene studies reported 30 different genes that were associated (p < 0.05) with physical activity or sedentary behaviour. SNPs in or close to nine candidate genes were associated with physical activity or sedentary behaviour in more than one study.

CONCLUSION

GWAS have reported up to 10 loci associated with physical activity or sedentary behaviour. Candidate gene studies have pointed to some interesting genetic variants, but few have been replicated. Our review highlights the need for high-quality GWAS in large population-based samples, and with objectively assessed phenotypes, in order to establish robust genetic instruments for physical activity and sedentary behaviour. Furthermore, consistent replications in GWAS are needed to improve credibility of genetic variants.

TRIAL REGISTRATION

Prospero CRD42019119456 .

Genomewide Association Study of Leisure-Time Exercise Behavior in Japanese Adults

Supplemental digital content is available in the text.

Purpose

Although several genetic factors may play a role in leisure-time exercise behavior, there is currently no evidence of a significant genomewide association, and candidate gene replication studies have produced inconsistent results.

Methods

We conducted a two-stage genomewide association study and candidate single-nucleotide polymorphisms (SNP) association study on leisure-time exercise behavior using 13,980 discovery samples from the Japan Multi-Institutional Collaborative Cohort (J-MICC) study, and 2036 replication samples from the Hospital-based Epidemiologic Research Program at Aichi Cancer Center-2 study. Leisure-time physical activity was measured using a self-administered questionnaire that inquired about the type, frequency and duration of exercise. Participants with ≥4 MET·h·wk⁻¹ of leisure-time physical activity were defined as exhibiting leisure-time exercise behavior. Association testing using mixed linear regression models was performed on the discovery and replication samples, after which the results were combined in a meta-analysis. In addition, we tested six candidate genetic variants derived from previous genomewide association study.

Results

We found that one novel SNP (rs10252228) located in the intergenic region between NPSR1 and DPY19L1 was significantly associated with leisure-time exercise behavior in discovery samples. This association was also significant in replication samples (combined P value by meta-analysis = 2.2 × 10⁻⁹). Several SNP linked with rs10252228 were significantly associated with gene expression of DPY19L1 and DP19L2P1 in skeletal muscle, heart, whole blood, and the nervous system. Among the candidate SNP, rs12612420 in DNAPTP6 demonstrated nominal significance in discovery samples but not in replication samples.

Conclusions

We identified a novel genetic variant associated with regular leisure-time exercise behavior. Further functional studies are required to validate the role of these variants in exercise behavior.

Genetic Factors Associated With Human Physical Activity: Are Your Genes Too Tight To Prevent You Exercising?

The benefits of physical activity (PA) on health and fitness are well known. It has become apparent from studies of heritability that there is a considerable genetic component to PA. However, PA is such a complex phenotype that the measurement and quantification of it provide a challenge to a clearer understanding of its genetic basis. In this review, we assessed available evidence from family and twin studies that have estimated the heritability of PA. Heritability is greater when evaluated by accelerometry compared with questionnaires, and for questionnaires higher in twin than family studies. Accelerometry studies suggest heritability of PA is 51% to 56%. There have been many genome-wide linkage studies, candidate gene studies, and four genome-wide association studies that have highlighted specific genetic factors linked to different PA levels. These studies have generally failed to replicate identified loci, with the exception of the melanocortin 4 receptor, and this may be because of the variability in the measurement techniques used to characterize the behavior. Future work should aim to standardize the procedures used to measure PA in the context of trying to identify genetic causes. The link of genetics to physical exercise is not so tight that it prevents voluntary interventions.

Effect of Interaction between Early Menarche and Genetic Polymorphisms on Triglyceride

Early menarche has been associated with increased risk of metabolic syndrome. Therefore, investigating the association of each component of metabolic syndrome with age at menarche, and interactions between them, might lead to a better understanding of metabolic syndrome pathogenesis. In this study, we evaluated age at menarche for risk of metabolic syndrome and associations with its components. As a result, the risk of MetS incidence was significantly increased only at ≤12 years of age at menarche (OR = 1.91, P < 0.05). Women with early menarche (≤12 years) had significantly higher levels of triglycerides (β coefficient = 37.83, P = 0.02). In addition, hypertriglyceridemia was significantly increased at early menarche with 1.99 (95% CI: 1.16–3.41, P < 0.01). With GWAS-based pathway analysis, we found the type 2 diabetes mellitus, stress-activated protein kinase signaling, and Jun amino-terminal kinase cascade pathways (all nominal P < 0.001, all FDR < 0.05) to be significantly involved with early menarche on triglyceride levels. These findings may help us understand the role of early menarche on triglyceride and interaction between gene and early menarche on triglyceride for the development of metabolic syndrome.

Androgen and estrogen actions on male physical activity: a story beyond muscle

Physical inactivity is a pandemic that contributes to several chronic diseases and poses a significant burden on health care systems worldwide. The search for effective strategies to combat sedentary behavior has led to an intensification of the research efforts to unravel the biological substrate controlling activity. A wide body of preclinical evidence makes a strong case for sex steroids regulating physical activity in both genders, albeit the mechanisms implicated remain unclear. The beneficial effects of androgens on muscle as well as on other peripheral functions might play a role in favoring adaptation to exercise. Alternatively or in addition, sex steroids could act on specific brain circuitries to boost physical activity. This review critically discusses the evidence supporting a role for androgens and estrogens stimulating male physical activity, with special emphasis on the possible role of peripheral and/or central mechanisms. Finally, the potential translation of these findings to humans is briefly discussed.

Genome-wide association study of habitual physical activity in over 377,000 UK Biobank participants identifies multiple variants including CADM2 and APOE

BACKGROUND/OBJECTIVES

Physical activity (PA) protects against a wide range of diseases. Habitual PA appears to be heritable, motivating the search for specific genetic variants that may inform efforts to promote PA and target the best type of PA for each individual.

SUBJECTS/METHODS

We used data from the UK Biobank to perform the largest genome-wide association study of PA to date, using three measures based on self-report (nmax = 377,234) and two measures based on wrist-worn accelerometry data (nmax = 91,084). We examined genetic correlations of PA with other traits and diseases, as well as tissue-specific gene expression patterns. With data from the Atherosclerosis Risk in Communities (ARIC; n = 8,556) study, we performed a meta-analysis of our top hits for moderate-to-vigorous PA (MVPA).

RESULTS

We identified ten loci across all PA measures that were significant in both a basic and a fully adjusted model (p < 5 × 10-9). Upon meta-analysis of the nine top hits for MVPA with results from ARIC, eight were genome-wide significant. Interestingly, among these, the rs429358 variant in the APOE gene was the most strongly associated with MVPA, whereby the allele associated with higher Alzheimer's risk was associated with greater MVPA. However, we were not able to rule out possible selection bias underlying this result. Variants in CADM2, a gene previously implicated in obesity, risk-taking behavior and other traits, were found to be associated with habitual PA. We also identified three loci consistently associated (p < 5 × 10-5) with PA across both self-report and accelerometry, including CADM2. We found genetic correlations of PA with educational attainment, chronotype, psychiatric traits, and obesity-related traits. Tissue enrichment analyses implicate the brain and pituitary gland as locations where PA-associated loci may exert their actions.

CONCLUSIONS

These results provide new insight into the genetic basis of habitual PA, and the genetic links connecting PA with other traits and diseases.

Interaction between physical activity, PITX1 rs647161 genetic polymorphism and colorectal cancer risk in a Korean population: a case-control study

This study assessed the interaction between physical activity and colorectal cancer (CRC) risk based on a polymorphism in the paired-like homeodomain 1 (PITX1) gene in Koreans. In total, 923 cases and 1,846 controls were enrolled at the National Cancer Center, Korea. Subjects who did regular exercise showed a significantly reduced risk of CRC than those did not exercise regularly (OR = 0.37, 95% CI = 0.30-0.45). Subjects in the highest tertile of metabolic equivalents of task (MET)-minutes per week showed a significantly lower risk of CRC (OR = 0.62, 95% CI = 0.48-0.79, p-trend < 0.001). In the dominant model, minor allele carriers showed a significantly higher risk of CRC than subjects homozygous for the major allele (OR = 1.46, 95% CI = 1.18-1.80). The PITX1 genetic variant showed significant interactions with regular exercise and CRC risk (p-interaction = 0.018) and colon cancer risk (p-interaction = 0.029) among all subjects. Subjects who carried at least one minor allele and did not regularly exercise showed a greater risk of CRC (OR = 1.81, 95% CI = 1.37-2.41). Subjects who were homozygous for the major allele with high physical activity showed a significantly reduced risk of CRC (OR = 0.56, 95% CI = 0.38-0.82). Thus, individuals with PITX1 genetic variants can have benefit from physical activity regarding prevention of CRC risk in a Korean population.

Limited potential of genetic predisposition scores to predict muscle mass and strength performance in Flemish Caucasians between 19 and 73 years of age

Since both muscle mass and strength performance are polygenic in nature, the current study compared four genetic predisposition scores (GPS) in their ability to predict these phenotypes. Data were gathered within the framework of the first-generation Flemish Policy Research Centre "Sport, Physical Activity and Health" (2002-2004). Results are based on muscle characteristics data of 565 Flemish Caucasians (19-73 yr, 365 men). Skeletal muscle mass was determined from bioelectrical impedance. The Biodex dynamometer was used to measure isometric (PT_static120°) and isokinetic strength (PT_dynamic60° and PT_dynamic240°), ballistic movement speed (S_20%), and muscular endurance (Work) of the knee extensors. Genotyping was done for 153 gene variants, selected on the basis of a literature search and the expression quantitative trait loci of selected genes. Four GPS were designed: a total GPS (based on the sum of all 153 variants, each favorable allele = score 1), a data-driven and weighted GPS [respectively, the sum of favorable alleles of those variants with significant b-coefficients in stepwise regression (GPS_dd), and the sum of these variants weighted with their respective partial r² (GPS_w)], and an elastic net GPS (based on the variants that were selected by an elastic net regularization; GPS_en). It was found that four different models for a GPS were able to significantly predict up to ~7% of the variance in strength performance. GPS_en made the best prediction of SMM and Work. However, this was not the case for the remaining strength performance parameters, where best predictions were made by GPS_dd and GPS_w.