No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Sports genetics moving forward: Lessons learned from medical research
Abstract
Sports genetics can take advantage of lessons learned from human disease genetics. By righting past mistakes and increasing scientific rigor, the breadth and depth of knowledge in the field can be magnified. We present an outline of challenges facing sports genetics in the light of experiences from medical research. Sports performance is complex, resulting from a combination of a wide variety of different traits and attributes. Improving sports genetics will foremost require analyses based on detailed phenotyping. In order to find widely valid, reproducible common variants associated with athletic phenotypes, study sample sizes must be dramatically increased. One paradox is that in order to confirm relevance, replications in specific populations must be undertaken. Family studies of athletes may facilitate the discovery of rare variants with large effects on athletic phenotypes. The complexity of the human genome, combined with the complexity of athletic phenotypes, will require additional metadata and biological validation to identify a comprehensive set of genes involved. Analysis of personal genetic and multiomic profiles contribute to our conceptualization of precision medicine; the same will be the case in precision sports science. In the refinement of sports genetics it is essential to evaluate similarities and differences between genders and among ethnicities. Sports genetics to date have been hampered by small sample sizes and biased methodology which can lead to erroneous associations and overestimation of effect sizes. Consequently, currently available genetic tests based on these inherently limited data cannot predict athletic performance with any accuracy.
... (Lippi et al., 2010) 3.3 Cluster: weaknesses 3.3.1 Theme: quality of studies Most Weaknesses identified by the thematic analysis were related to methodological shortcomings resulting from "low quality studies." (Brutsaert and Parra, 2006;Ostrander et al., 2009;Wackerhage et al., 2009;Rankinen et al., 2010;Bouchard, 2011;Bouchard et al., 2011;Eynon et al., 2011;Hagberg et al., 2011;Roth et al., 2012;Guth and Roth, 2013;Wang et al., 2013;Breitbach et al., 2014;Ahmetov and Fedotovskaya, 2015;Bouchard, 2015;Loos et al., 2015;Webborn et al., 2015;Gibson, 2016;Mattsson et al., 2016;Pitsiladis et al., 2016;Wang et al., 2016;Moran and Pitsiladis, 2017;Vlahovich et al., 2017;Vellers et al., 2018;Landen et al., 2019;Gomes et al., 2020;Naureen et al., 2020;Tanisawa et al., 2020;Griswold et al., 2021;Kim et al., 2022;Varillas-Delgado et al., 2022) Numerous scholars have contended that the present body of knowledge in the field of sport genetics/genomics is primarily rooted in investigations of candidate genes (i.e., research designed to test a priori hypotheses using casecontrol designs), which typically involve limited sample sizes and, as a result, frequently exhibit insufficient statistical power. (Brutsaert and Parra, 2006;Wang et al., 2013;Ahmetov and Fedotovskaya, 2015;Loos et al., 2015;Mattsson et al., 2016;Pitsiladis et al., 2016;Yan et al., 2016;Moran and Pitsiladis, 2017;Vlahovich et al., 2017) Some authors acknowledged that candidate gene studies produced "inconclusive results" or "false positives" (Wang et al., 2013;Ahmetov and Fedotovskaya, 2015;Loos et al., 2015;Gibson, 2016;Mattsson et al., 2016;Moran and Pitsiladis, 2017;Varillas-Delgado et al., 2022). ...
... (Brutsaert and Parra, 2006;Ostrander et al., 2009;Wackerhage et al., 2009;Rankinen et al., 2010;Bouchard, 2011;Bouchard et al., 2011;Eynon et al., 2011;Hagberg et al., 2011;Roth et al., 2012;Guth and Roth, 2013;Wang et al., 2013;Breitbach et al., 2014;Ahmetov and Fedotovskaya, 2015;Bouchard, 2015;Loos et al., 2015;Webborn et al., 2015;Gibson, 2016;Mattsson et al., 2016;Pitsiladis et al., 2016;Wang et al., 2016;Moran and Pitsiladis, 2017;Vlahovich et al., 2017;Vellers et al., 2018;Landen et al., 2019;Gomes et al., 2020;Naureen et al., 2020;Tanisawa et al., 2020;Griswold et al., 2021;Kim et al., 2022;Varillas-Delgado et al., 2022) Numerous scholars have contended that the present body of knowledge in the field of sport genetics/genomics is primarily rooted in investigations of candidate genes (i.e., research designed to test a priori hypotheses using casecontrol designs), which typically involve limited sample sizes and, as a result, frequently exhibit insufficient statistical power. (Brutsaert and Parra, 2006;Wang et al., 2013;Ahmetov and Fedotovskaya, 2015;Loos et al., 2015;Mattsson et al., 2016;Pitsiladis et al., 2016;Yan et al., 2016;Moran and Pitsiladis, 2017;Vlahovich et al., 2017) Some authors acknowledged that candidate gene studies produced "inconclusive results" or "false positives" (Wang et al., 2013;Ahmetov and Fedotovskaya, 2015;Loos et al., 2015;Gibson, 2016;Mattsson et al., 2016;Moran and Pitsiladis, 2017;Varillas-Delgado et al., 2022). Furthermore, Kim et al. (2020) (Kim et al., 2022) highlighted that "only a handful of genome-wide association studies" have been performed in a exercise science context, and according to Griswold et al., (2021) (Griswold et al., 2021) "even the largest genome-wide association study to date in elite endurance athletes (a total of 1,520 athletes and 2,760 controls) was not able to identify any significantly associated genetic markers". ...
... (Brutsaert and Parra, 2006;Ostrander et al., 2009;Wackerhage et al., 2009;Rankinen et al., 2010;Bouchard, 2011;Bouchard et al., 2011;Eynon et al., 2011;Hagberg et al., 2011;Roth et al., 2012;Guth and Roth, 2013;Wang et al., 2013;Breitbach et al., 2014;Ahmetov and Fedotovskaya, 2015;Bouchard, 2015;Loos et al., 2015;Webborn et al., 2015;Gibson, 2016;Mattsson et al., 2016;Pitsiladis et al., 2016;Wang et al., 2016;Moran and Pitsiladis, 2017;Vlahovich et al., 2017;Vellers et al., 2018;Landen et al., 2019;Gomes et al., 2020;Naureen et al., 2020;Tanisawa et al., 2020;Griswold et al., 2021;Kim et al., 2022;Varillas-Delgado et al., 2022) Numerous scholars have contended that the present body of knowledge in the field of sport genetics/genomics is primarily rooted in investigations of candidate genes (i.e., research designed to test a priori hypotheses using casecontrol designs), which typically involve limited sample sizes and, as a result, frequently exhibit insufficient statistical power. (Brutsaert and Parra, 2006;Wang et al., 2013;Ahmetov and Fedotovskaya, 2015;Loos et al., 2015;Mattsson et al., 2016;Pitsiladis et al., 2016;Yan et al., 2016;Moran and Pitsiladis, 2017;Vlahovich et al., 2017) Some authors acknowledged that candidate gene studies produced "inconclusive results" or "false positives" (Wang et al., 2013;Ahmetov and Fedotovskaya, 2015;Loos et al., 2015;Gibson, 2016;Mattsson et al., 2016;Moran and Pitsiladis, 2017;Varillas-Delgado et al., 2022). Furthermore, Kim et al. (2020) (Kim et al., 2022) highlighted that "only a handful of genome-wide association studies" have been performed in a exercise science context, and according to Griswold et al., (2021) (Griswold et al., 2021) "even the largest genome-wide association study to date in elite endurance athletes (a total of 1,520 athletes and 2,760 controls) was not able to identify any significantly associated genetic markers". ...
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.
... A larger sample size could reveal these relationships. Unfortunately, the sample size is a common problem in genetic research in sport because of the small number of subjects who are successful in a given discipline and simultaneously come from the same country (22,38). It cannot be ruled out however that this gene can have different effects on the performance depending on sex (21,22,38). ...
... Unfortunately, the sample size is a common problem in genetic research in sport because of the small number of subjects who are successful in a given discipline and simultaneously come from the same country (22,38). It cannot be ruled out however that this gene can have different effects on the performance depending on sex (21,22,38). ...
... This study has some strengths but also some limitations. The limitation of this study is the small sample size, which is a common problem in genetic research (22,38). On the other hand, the strengths of our study are the ethnically homogeneous group, highly selected endurance athletes, especially in rowing, and simultaneous examination of hematological indicators, including the best marker of the quantitative assessment of hemoglobin in the circulation (tHbmass), as well as intravascular volumes and aerobic capacity indices. ...
Malczewska-Lenczowska, J, Orysiak, J, Majorczyk, E, Sitkowski, D, Starczewski, M, and Żmijewski, P. HIF-1α and NFIA-AS2 polymorphisms as potential determinants of total hemoglobin mass in endurance athletes. J Strength Cond Res 36(6): 1596-1604, 2022-The aims of this study were to examine (1) the genotype distribution of rs11549465:C>T of the HIF-1α gene and rs1572312:C>A of the NFIA-AS2 gene; (2) the association between the genes and hematological status in endurance-oriented athletes; and (3) the association between the NFIA-AS2 gene and aerobic capacity in cyclists. Two hundred thirty-eight well-trained athletes (female n = 90, male n = 148) participated in the study. Total hemoglobin mass (tHbmass), blood morphology, intravascular volumes, i.e., erythrocyte volume (EV), blood volume (BV) and plasma volume (PV), and aerobic capacity indices, e.g., peak oxygen uptake (V̇o2peak), and power at anaerobic threshold (PAT) were determined. In both studied genes, the CC genotype was predominant. In the HIF-1α gene, there were no differences in genotype and allele distribution among athletes from different disciplines and between sexes. The distribution of genotypes and alleles of the NFIA-AS2 gene differed significantly in male athletes; the frequency of A allele carriers (CA + AA) was significantly higher in cyclists than in rowers and middle- and long-distance runners. The athletes with CC genotype of NF1A-AS2 had significantly higher relative values of: tHbmass (total female athletes, cyclists), PV, BV (cyclists), and EV (total male athletes, cyclists) and PAT (cyclists) than A allele carriers (CA + AA genotypes). In conclusion, our study indicates that NFIA-AS2 rs1572312:C>A polymorphism was associated with hematological status in endurance athletes, as well as aerobic capacity indices in male cyclists. It suggests that this polymorphism may be a determinant of quantity of hemoglobin and intrtavascular volumes, which in turn can have an impact on aerobic performance.
... This is before considering simple serendipity (i.e., low probability events). Overall, athletic performance is a qualitative phenotype, not a physiological measurement (Mattsson et al., 2016). Table 1 Genetic testing best practice guidelines for practitioners in sport. ...
... collaboration on this scale may also exacerbate the heterogeneity of athlete samples in terms of factors such as competitive playing level, sport discipline, geographic ancestry, on-field playing position, sex, chronological age, maturity status, and phenotype measurement. Cohort homogeneity is vitally important in sports genomic research, as each of these factors can have a confounding influence on genotype-phenotype associations(Guilherme et al., 2014;Mattsson et al., 2016;Tanisawa et al., 2020).Bringing cohorts together from different countries also requires researchers to carefully consider what criteria should be used to categorise athletes into competitive groups (e.g., elite, sub-elite, non-elite). Sports differ in terms of popularity and development across nations, so the performance level of athletes will need to beassessed relative to the competition pool both inside and outside their own country (McAuley, Baker, & Kelly, 2022; McKay et al., 2022). ...
Current scientific evidence does not support the implementation of genetic tests to enhance the processes of talent identification and development systems. Regardless of this consensus, it appears likely that sport stakeholders will continue using genetic tests. This paper aimed to provide practitioners with some best practice guidelines if implementing genetic testing within their organisations. First, we assess the growth and perceived flaws of direct-to-consumer genetic testing companies targeted towards sport. The sports genomic literature is then summarised to demonstrate the lack of established genetic associations with sporting phenotypes and the prevalent limitations that exist in this field of research. Following this, examples are presented suggesting some stakeholders in sport have already used genetic tests to screen for variants associated with performance phenotypes, while the potential appeal of genetic information to sport stakeholders is also discussed. The value of increased genetic literacy (i.e., enhanced education/understanding of genetic information) is then considered, as well as the promotion of talent inclusion (i.e., using genetic tests to include or retain athletes rather than for de-selection and exclusion purposes). To conclude, we offer practitioners several recommendations and best practice guidelines with regards to the implementation of genetic testing in sport.
... These attempts, e.g., in the field of precision medicine, are based on prediction models and the predictive ability of these models tend to increase with the amount and quality of data input [17]. Thus, from a "precision endurance exercise" perspective, the more factors associated with high-level endurance performance are integrated, the better the prediction of the model should become as evidenced in medical research [18]. ...
... The predictive ability of such models tends to increase with the amount and quality of data input [17]. Hence, the identification of key factors and integration into future models the better the predictions will become [18]. Moreover, the current findings can be integrated into new technology such as wearables for data-informed decision-making enabling endurance athletes and coaches to monitor the athletes' health, risk of injury, and performance in real time [57]. ...
There is little agreement on the factors influencing endurance performance. Endurance performance often is described by surrogate variables such as maximum oxygen consumption, lactate threshold, and running economy. However, other factors also determine success and progression of high-level endurance athletes. Therefore, the aim was to identify the relevant factors for endurance performance assessed by international experts by adhering to a structured communication method (i.e., Delphi technique). Three anonymous evaluation rounds were conducted initiated by a list of candidate factors (n = 120) serving as baseline input variables. The items that achieved ≥70% of agreement in round 1 were re-evaluated in a second round. Items with a level of agreement of ≥70% in round 2 reached consensus and items with a level of agreement of 40–69% in round 2 were re-rated in a third round followed by a consensus meeting. Round 1 comprised of 27 panellists (n = 24 male) and in round 2 and 3 18 (n = 15 male) of the 27 panellists remained. Thus, the final endurance expert panel comprised of 18 international experts (n = 15 male) with 20 years of experience on average. The consensus report identified the following 26 factors: endurance capacity, running economy, maximal oxygen consumption, recovery speed, carbohydrate metabolism, glycolysis capacity, lactate threshold, fat metabolism, number of erythrocytes, iron deficiency, muscle fibre type, mitochondrial biogenesis, hydrogen ion buffering, testosterone, erythropoietin, cortisol, hydration status, vitamin D deficiency, risk of non-functional overreaching and stress fracture, healing function of skeletal tissue, motivation, stress resistance, confidence, sleep quality, and fatigue. This study provides an expert-derived summary including 26 key factors for endurance performance, the “FENDLE” factors (FENDLE = Factors for ENDurance Level). This consensus report may assist to optimize sophisticated diagnostics, personalized training strategies and technology.
... Yet, carriers of the NOS3 C 786 MA had a more exaggerated peak systolic BP (SBP) response to a maximal graded exercise test (GEST) than men with the NOS3 TT genotype (Olson et al. 2012). A significant limitation of this candidate gene approach is that initial findings of BP-genotype associations often are not confirmed in follow-up studies (Bouchard 2011;Bouchard et al. 2012;Ash et al. 2013a,b;Bruneau et al. 2016;Mattsson et al. 2016). Therefore, in a replication cohort, we utilize genomic technology that was not available when we performed our discovery phase candidate gene association studies to confirm if NOS3 variants exhibit exercise intensity-dependent associations with PEH. ...
... In addition, we employed several methodological strategies to improve the statistical power to find NOS3 genotype-BP associations should they exist (Bouchard 2011;Ash et al. 2013a;Bruneau et al. 2016;Mattsson et al. 2016;Pescatello et al. 2016). Our strategies were use of: a repeated measure design that modeled the withinsubject correlation of the 19 hourly time points, a targeted inquiry of polymorphisms with a prioritized panel of genes that reduced the genomic search space, highthroughput exon sequencing to target functional regions of the gene, and the same standardized protocols and methods in our discovery phase and replication studies. ...
In previous studies, we found an endothelial nitric oxide synthase gene (NOS3) variant rs2070744 associated with the ambulatory blood pressure (BP) response following bouts of moderate and vigorous intensity acute exercise, termed post-exercise hypotension (PEH). In a validation cohort, we sequenced NOS3 exons for associations with PEH. Obese (30.9 ± 3.6 kg.m−2) African American (n = 14) [AF] and Caucasian (n = 9) adults 42.0 ± 9.8 years with hypertension (139.8 ± 10.4/84.6 ± 6.2 mmHg) performed three random experiments: bouts of vigorous and moderate intensity cycling and control. Subjects were attached to an ambulatory BP monitor for 19 h. We performed deep-targeted exon sequencing with the Illumina TruSeq Custom Amplicon kit. Variant genotypes were coded as number of minor alleles (#MA) and selected for additional statistical analysis based upon Bonferonni or Benjamini–Yekutieli multiple testing-corrected P-values under time-adjusted linear models for 19 hourly BP measurements for each subject. After vigorous intensity over 19 h, among NOS3 variants passing multiple testing thresholds, as the #MA increased in rs891512 (P = 6.4E-04), rs867225 (P = 6.5E-04), rs743507 (P = 2.6E-06), and rs41483644 (P = 2.4E-04), systolic (SBP) decreased from 17.5 to 33.7 mmHg; and in rs891512 (P = 9.7E-05), rs867225 (P = 2.6E-05), rs41483644 (P = 1.6E-03), rs3730009 (P = 2.6E-04), and rs77325852 (P = 5.6E-04), diastolic BP decreased from 11.1 mmHg to 20.3 mmHg among AF only. In contrast, after moderate intensity over 19 h in NOS3 rs3918164, as the #MA increased, SBP increased by 16.6 mmHg (P = 2.4E-04) among AF only. NOS3 variants exhibited associations with PEH after vigorous, but not moderate intensity exercise among AF only. NOS3 should be studied further for its effects on PEH in a large, ethnically diverse sample of adults with hypertension to confirm our findings.
... Angiotensin-converting enzyme gene (ACE) which had concluded that one of the polymorphic alleles of ACE gene is allele-I provides tolerance, and allele-D -speed-power qualities of athlete, on the basis of higher frequency of alleles in athletes, successful in their respective sports in relation to the control group [17]. However, in the future, a number of authors will find no differences in the frequency of occurrence of genotypes in athletes and people who are not involved in sports [18,19]. Nevertheless, differences will be appeared in the analysis of the study in athletes' genotypes, specializing in several sport fields [20]. ...
... To improve the effectiveness of sports genetics primarily will require analysis based on a detailed full [17,18]. ...
During the last two decades, sports medicine is increased and experienced a stage of rapid development, especially in such areas as the study of strength, endurance, sports injuries and psychology. Study of ongoing changes when performing exercises at the cellular and molecular levels led to the development of new areas in the sports science as known as genetic medicine that deals with the genetic basis of athletic phenotype. Around 66 % of the variance in athlete status is explained by genetic factors, the remaining variance is due to other factors such as training, nutrition, equipment, motivation, sleeping and epigenetics. Over the last two decades, at least 155 genetic markers (located in almost all chromosomes and mtDNA) were associated with elite athlete status (93 genetic markers with endurance and 62 markers with power/force). The number of identified genetic markers associated with sports activity, grew at a rate exponentially: in 1997 – 5 genes; in 2000 – 24 genes; in 2004 – 101 genes. During the last 19 years, found that at least 120 of genetic markers associated with elite athlete status (77 genetic markers related to endurance and 43 genetic marker settings capacity/power). Of the polymorphisms associated with sports endurance, the angiotensin-converting enzyme (ACE) and alpha actinin-3 (ACTN3) polymorphisms have been the most frequently studied, and meta-analyses have confirmed the associations. ACTN3 is absent in approximately 18% of European population, 25-29% of Japanese population and overall about 1.5 billion people in all countries. Therefore, to date, available genetic tests based on small sample sizes and the selected analytical methodology can lead to erroneous associations and to reassess the size of the effect, and of course, the use of such limited data does not allow us to predict athletic ability with high accuracy.
... We recently conducted a meta-analysis of candidate gene association studies examining the BP response to acute (i.e., PEH) and chronic (i.e., training) aerobic exercise and found that Angiotensiogen (AGT) rs699 emerged as the only promising variant to explore further (Bruneau et al. 2015). This finding substantiates a major concern of candidate gene association studies that examine the response of health-related phenotypes to exercise; that is, most statistically significant findings fail to replicate due to a variety of factors that include the lack of standardized protocols, statistical adjustments for multiple comparisons, and adequately powered samples (Bouchard 2011;Bouchard et al. 2012;Ash et al. 2013a;Bruneau et al. 2015;Mattsson et al. 2016). ...
... In addition, we instituted methodological strategies to increase the statistical power to detect renal genotype-BP associations should they exist (Bouchard 2011;Ash et al. 2013a;Bruneau et al. 2015;Mattsson et al. 2016). These strategies included a repeated measure design among the same individuals that increased the number of observations per subject by 19 hourly time points, a focused inquiry of polymorphisms with a prioritized panel of genes that reduced the search space within the genome, performing high throughput exon sequencing to focus on functional regions of the gene, and inclusion of the same standardized protocols and methods in our discovery phase and replication studies. ...
We found variants from the Angiotensinogen-Converting Enzyme (ACE), Angiotensin Type 1 Receptor (AGTR1), Aldosterone Synthase (CYP11B2), and Adducin (ADD1) genes exhibited intensity-dependent associations with the ambulatory blood pressure (BP) response following acute exercise, or postexercise hypotension (PEH). In a validation cohort, we sequenced exons from these genes for their associations with PEH. Obese (30.9 ± 3.6 kg m−2) adults (n = 23; 61% African Americans [AF], 39% Caucasian) 42.0 ± 9.8 years with hypertension (139.8 ± 10.4/84.6 ± 6.2 mmHg) completed three random experiments: bouts of vigorous and moderate intensity cycling and control. Subjects wore an ambulatory BP monitor for 19 h. We performed deep-targeted exon sequencing using the Illumina TruSeq Custom Amplicon kit. Variant genotypes were coded as number of minor alleles (#MA) and selected for further statistical analysis based upon Bonferonni or Benjamini–Yekutieli multiple testing corrected p-values under time adjusted linear models for 19 hourly BP measurements per subject. After vigorous intensity over 19 h among ACE, AGTR1, CYP11B2, and ADD1 variants passing multiple testing thresholds, as the #MA increased, systolic (SBP) and/or diastolic BP decreased 12 mmHg (P = 4.5E-05) to 30 mmHg (P = 6.4E-04) among AF only. In contrast, after moderate intensity over 19 h among ACE and CYP11B2 variants passing multiple testing thresholds, as the #MA increased, SBP increased 21 mmHg (P = 8.0E-04) to 22 mmHg (P = 8.2E-04) among AF only. In this replication study, ACE, AGTR1, CYP11B2, and ADD1 variants exhibited associations with PEH after vigorous, but not moderate intensity exercise among AF only. Renal variants should be explored further with a multi-level “omics” approach for associations with PEH among a large, ethnically diverse sample of adults with hypertension.
... For example, the ACE gene is linked to endurance, while ACTN3 is associated with strength. However, genetic test results for athletes should be interpreted cautiously, as each genetic variant explains only a small portion of performance, with factors like training volume, organization, nutrition, daily routine, and other environmental factors playing a much larger role [15]. ...
Identifying and studying genetic polymorphisms that determine the phenotype of elite athletes is a highly relevant task, as it forms the basis for developing so-called sports genetic passports. The aim of this manuscript was to analyze genetic markers for the development of athletic qualities (strength, power, speed, and endurance) through a selective systematic review of the literature. This review allowed to select SNPs that are responsible for individual athletic qualities based on the functions of their gene products, proposing an interpretation of sports markers for genetic passports. These markers can provide scientists in physical culture and sports medicine with the latest and most compelling evidence in the field of exercise genomics. A panel of 40 of the most popular genetic markers associated with athletic performance, responsible for strength, speed, and endurance, has been presented.
... This is underpinned by the complexity of gene-gene and gene-environment interactions, as well as the multifactorial and dynamic nature of athlete development [3,19,31,37]. Therefore, as high-performance is not an isolated, independent, or static trait, expertise in the sporting domain may never be fully quantifiable or predicted accurately via any performance measuring metric, including genetic information [8,16]. As a result, key stakeholders in professional football are recommended to act with caution when utilising genetic testing for these purposes, whilst researchers are encouraged to design, implement, and evaluate methods of education. ...
Purpose
Genetic research in football is currently in it’s infancy but is growing rapidly. However, the practical application of genetic testing in football and the views concerning its use are unknown. Thus, the purpose of this study was to assess the current practical application of genetic testing in professional football and provide an insight into the perspectives of key stakeholders (i.e., coaches, practitioners, players).
Methods
In total, 122 participants completed an online anonymous survey. This consisted of 21 multiple choice and Likert scale questions, with the option of providing an explanation for each response.
Results
Findings revealed genetic testing is rarely utilised by key stakeholders (10%) or their respective organisations (14%). However, three quarters (75%) had the opinion that genetic testing will have great utility in the future. The majority (72%) believed genetic testing should be used for athlete development and injury risk, whilst 35% believed that genetic testing should be utilised for talent identification purposes. However, most key stakeholders viewed their own (89%) and their colleagues’ (79%) knowledge related to genetic testing as insufficient; mainly due to ineffective current communication methods (91%). Most believed educational workshops are required (71%), whilst nearly all (91%) were interested in developing their expertise on the utility of genetic testing.
Conclusion
Genetic testing is rarely used within professional football, although key stakeholders anticipate that it will be utilised more in the future. As such, educational support may prove valuable in improving key stakeholder knowledge and the practical application of genetic testing in professional football.
... Его варианты могут быть связаны с улучшенными показателями в видах спорта, требующих длительной физической нагрузки. Например, мутация R577X в гене ACTN3 ассоциирована с острым растяжением голеностопного сустава [48,49]. ...
The mechanical properties of tendons are thought to be affected by different loading levels. Changes in the mechanical properties of tendons, such as stiffness, have been reported to influence the risk of tendon injuries chiefly in athletes and the elderly, thereby affecting motor function execution. Unloading resulted in reduced tendons stiffness, and resistance exercise exercise counteracts this. Transforming growth factor-1 is a potent inducer of type I collagen and mechanosensitive genes encoding tenogenic differentiation markers expression which play critical roles in tendon tissue formation, tendon healing and their adaptation during exercise. In recent years, our understanding of the molecular biology of tendons growth and repair has expanded. It is probable that the next advance in the treatment of tendon injuries will result from the application of this basic science knowledge and the clinical solution will encompass not only the the best postoperative rehabilitation protocols, but also the optimal biological modulation of the healing process.
... As a result, it appears likely that, in order to successfully predict future elite athlete status, models involving genetic variants with low effect sizes are likely required. However, the common issue of sample size returns; for discovery of relatively common genetic variants with small effect sizes, sample sizes in excess of 10,000 individuals are likely required(Mattsson et al., 2016)-a number likely greater than that of all truly elite athletes on the planet. ...
Variation between individuals in response to a stimulus is a well-established phenomenon. This thesis discusses the drivers of this inter-individual response, identifying three major determinants; genetic, environmental, and epigenetic variation between individuals. Focusing on genetic variation, the thesis explores how this information may be useful in elite sport, aiming to answer the question “Is there utility to genetic information in elite sport?” The current literature was critically analysed, with a finding that the majority of exercise genomics research explains what has happened previously, as opposed to assisting practitioners in modifying athlete preparation and enhancing performance. An exploration of the potential ways in which genetic information may be useful in elite sport then follows, including that of inter- individual variation in response to caffeine supplementation, the use of genetic information to assist in reducing hamstring injuries, and whether genetic information may help identify future elite athletes. These themes are then explored via empirical work. In the first study, an internet-based questionnaire assessed the frequency of genetic testing in elite athletes, finding that around 10% had undertaken such a test. The second study determined that a panel of five genetic variants could predict the magnitude of improvements in Yo-Yo test improvements following a standardised training programme in youth soccer players. The third study demonstrated the effectiveness of a panel of seven genetic variants in predicting the magnitude of neuromuscular fatigue in youth soccer players. The fourth and final study recruited five current or former elite athletes, including an Olympic Champion, and created the most comprehensive Total Genotype Score in the published literature to date, to determine whether their scores deviated significantly from a control population of over 500 non-athletes. The genetic panels were unable to adequately discriminate the elite performers from non-athletes, suggesting that, at this time, genetic testing holds no utility in the identification of future elite performers. The wider utilisation of genetic information as a public health tool is discussed, and a framework for the implementation of genetic information in sport is also proposed. In summary, this thesis suggests that there is great potential for the use of genetic information to assist practitioners in the athlete management process in elite sport, and demonstrates the efficacy of some commercially available panels, whilst cautioning against the use of such information as a talent identification tool. The major limitation of the current thesis is the low sample sizes of many of the experimental chapters, a common issue in exercise genetics research. Future work should aim to further explore the implementation of genetic information in elite sporting environments.
... As such, it appears that, in order to successfully predict future elite athlete status, models involving multiple genetic variants with low effect sizes are likely required, although this approach has recently been criticised from a disease-prediction viewpoint [58]. However, we return to the common issue of sample size; for discovery of relatively common genetic variants with small effect sizes, sample sizes in excess of 10,000 subjects are likely required [59]-a number considerably greater than that of all truly elite athletes within a specific performance trait on the planet. ...
Elite athlete status is a partially heritable trait, as are many of the underpinning physiological, anthropometrical, and psychological traits that contribute to elite performance. In recent years, our understanding of the specific genetic variants that contribute to these traits has grown, such that there is considerable interest in attempting to utilise genetic information as a tool to predict future elite athlete status. In this review, we explore the extent of the genetic influence on the making of a sporting champion and we describe issues which, at present, hamper the utility of genetic testing in identifying future elite performers. We build on this by exploring what further knowledge is required to enhance this process, including a reflection on the potential learnings from the use of genetics as a disease prediction tool. Finally, we discuss ways in which genetic information may hold utility within elite sport in the future, including guiding nutritional and training recommendations, and assisting in the prevention of injury. Whilst genetic testing has the potential to assist in the identification of future talented performers, genetic tests should be combined with other tools to obtain an accurate identification of those athletes predisposed to succeed in sport. The use of total genotype scores, composed of a high number of performance-enhancing polymorphisms, will likely be one of the best strategies in the utilisation of genetic information to identify talent in sport.
... As such, it appears that, in order to successfully predict future elite athlete status, models involving multiple genetic variants with low effect sizes are likely required, although this approach has recently been criticised from a disease-prediction viewpoint [58]. However, we return to the common issue of sample size; for discovery of relatively common genetic variants with small effect sizes, sample sizes in excess of 10,000 subjects are likely required [59]-a number considerably greater than that of all truly elite athletes within a specific performance trait on the planet. ...
Elite athlete status is a partially heritable trait, as are many of the underpinning physiological, anthropometrical, and psychological traits that contribute to elite performance. In recent years, our understanding of the specific genetic variants that contribute to these traits has grown, such that there is considerable interest in attempting to utilise genetic information as a tool to predict future elite athlete status. In this review, we explore the extent of the genetic influence on the making of a sporting champion and we describe issues which, at present, hamper the utility of genetic testing in identifying future elite performers. We build on this by exploring what further knowledge is required to enhance this process, including a reflection on the potential learnings from the use of genetics as a disease prediction tool. Finally, we discuss ways in which genetic information may hold utility within elite sport in the future, including guiding nutritional and training recommendations, and assisting in the prevention of injury. Whilst genetic testing has the potential to assist in the identification of future talented performers, genetic tests should be combined with other tools to obtain an accurate identification of those athletes predisposed to succeed in sport. The use of total genotype scores, composed of a high number of performance-enhancing polymorphisms, will likely be one of the best strategies in the utilisation of genetic information to identify talent in sport.
... Each individual human genome contains numerous genetic variants, which can be classified as rare or common based on their population frequency (i.e., rare variants are those that have frequencies ≤1%; Bansal et al., 2010). Although there are many rare variants of small/no effect (Mattsson et al., 2016), rare variants tend to exhibit larger biological effects than common variants (Bouchard, 2015). Here, we speculate that the rare T-allele of the SLC6A2 Thr99Ile variant may have an important negative psychobiological effect for power athletes. ...
Genetic variants in monoamine neurotransmitter genes have been recurrently associated with panic disorder, addiction and mood disorders. Recent evidence also indicates that norepinephrine neurotransmission can influence a series of psychophysical and psychobiological parameters related to athletic performance, and the presence of variants in the SLC6A2 (solute carrier family 6 member 2) gene, which encodes the norepinephrine transporter, can be detrimental to an adequate noradrenergic signaling. Accordingly, the objective of the present study was to explore the SLC6A2 Thr99Ile variant (rs1805065) in a cohort composed of highly-trained individuals and non-trained individuals. A total of 1556 Brazilians: 926 non-athletes and 630 athletes (322 endurance athletes and 308 power athletes) were compared in this case-control association study. The Thr99Ile variant showed only two genotypes (C/C or C/T), and a low minor allele frequency of ≈1%. However, none of the power athletes had the mutant T-allele (i.e., the C/T genotype), which may be related to decreased norepinephrine transporter activity. The genotype distribution and allele frequency observed in power athletes were significantly different when compared to non-athletes or endurance athletes. Therefore, the presence of the T-allele may decrease the chance of belonging to the group of athletes involved in explosive physical tasks. These results still need to be replicated in independent cohorts. However, it appears reasonable to assume that there is an association between the SLC6A2 gene variant and power athletic status.
... Improvements are also likely to come in the areas of improved biomedical testing (in immunological, oxidative stress-related fatigue and cardiovascular markers), improved clinician diagnoses, and field-based studies of race-related injuries and illnesses [87]. Personalized predictive medicine with a focus on genetics has arrived in clinical medicine, but will require additional metadata and biological validation to identify a comprehensive set of genes useful in sports [88]. Perception of injury and training risk factors among health professionals center primarily on training load and demographic characteristics. ...
Triathlon is characterized by the multidisciplinary nature of the sport where swimming, cycling, and running are completed sequentially in different events, such as the sprint, Olympic, long-distance, and Ironman formats. The large number of training sessions and overall volume undertaken by triathletes to improve fitness and performance can also increase the risk of injury, illness, or excessive fatigue. Short- and medium-term individualized training plans, periodization strategies, and work/rest balance are necessary to minimize interruptions to training due to injury, illness, or maladaptation. Even in the absence of health and wellbeing concerns, it is unclear whether cellular signals triggered by multiple training stimuli that drive training adaptations each day interfere with each other. Distribution of training intensity within and between different sessions is an important aspect of training. Both internal (perceived stress) and external loads (objective metrics) should be considered when monitoring training load. Incorporating strength training to complement the large body of endurance work in triathlon can help avoid overuse injuries. We explore emerging trends and strategies from the latest literature and evidence-based knowledge for improving training readiness and performance during competition in triathlon.
... Furthermore, common variants typically have small influences on a given trait. A thorough review [51] and a recent commentary [24] on sports genetics highlight the need for larger sample sizes, and both ethnicity-specific and sex-specific analyses to confirm effect sizes of common variants. ...
In recent years, the interest in personalised interventions such as medicine, nutrition, and exercise is rapidly rising to maximize health outcomes and ensure the most appropriate treatments. Exercising regularly is recommended for both healthy and diseased populations to improve health. However, there are sex-specific adaptations to exercise that often are not taken into consideration. While endurance exercise training alters the human skeletal muscle epigenome and subsequent gene expression, it is still unknown whether it does so differently in men and women, potentially leading to sex-specific physiological adaptations. Elucidating sex differences in genetics, epigenetics, gene regulation and expression in response to exercise will have great health implications, as it may enable gene targets in future clinical interventions and may better individualised interventions. This review will cover this topic and highlight the recent findings of sex-specific genetic, epigenetic, and gene expression studies, address the gaps in the field, and offer recommendations for future research.
... However, it is essential to underscore the distinction between the strength of evidence supporting DNA-based advice for personalized nutrition vs. that for fitness programming. Despite the fervent interest and ubiquity of commercial genetic testing to assess and improve exercise or sport performance (30)(31)(32), it should be noted that there is a lack of evidence encompassing exercise prescription and talent identification, such as the ability to predict the likelihood for the next generation of Olympians (33,34). Similarly, at this time there is insufficient evidence to recommended training protocols (strength or endurance) based on genotype or polygenic scores, that target specific fitness, weight loss or sport goals (35)(36)(37)(38). ...
An individual's dietary and supplement strategies can influence markedly their physical performance. Personalized nutrition in athletic populations aims to optimize health, body composition, and exercise performance by targeting dietary recommendations to an individual's genetic profile. Sport dietitians and nutritionists have long been adept at placing additional scrutiny on the one-size-fits-all general population dietary guidelines to accommodate various sporting populations. However, generic “one-size-fits-all” recommendations still remain. Genetic differences are known to impact absorption, metabolism, uptake, utilization and excretion of nutrients and food bioactives, which ultimately affects a number of metabolic pathways. Nutrigenomics and nutrigenetics are experimental approaches that use genomic information and genetic testing technologies to examine the role of individual genetic differences in modifying an athlete's response to nutrients and other food components. Although there have been few randomized, controlled trials examining the effects of genetic variation on performance in response to an ergogenic aid, there is a growing foundation of research linking gene-diet interactions on biomarkers of nutritional status, which impact exercise and sport performance. This foundation forms the basis from which the field of sport nutrigenomics continues to develop. We review the science of genetic modifiers of various dietary factors that impact an athlete's nutritional status, body composition and, ultimately athletic performance.
... However, their utility in predicting athletic ability remains highly questionable [20,21]. To date, most of these studies have utilized small sample sizes and focused on elite athletes [22]. For most of these genes, replication research has only inconsistently confirmed the causal link between particular genes and different types of athletic performance, let alone the predictive power of gene variants in the sports-choosing sphere [23][24][25]. ...
It remains unknown whether and how sports medicine physicians currently utilize genetic testing in their clinical practice. This study sought to assess knowledge of, experience with, and attitudes towards genetic testing by sports medicine physicians in the United States (US). An email with a survey hyperlink was distributed twice to members of the American Medical Society for Sports Medicine (AMSSM) listserv in September 2016, with approximately a 10% response rate. Questions focused on knowledge of, experience with, and attitudes towards testing for different genes related to sports proficiency, injury risk, and disease risk. Few AMSSM physicians believe that genetic testing to adapt training (12%) or to choose a sport (2%) is ready for clinical adoption. Most respondents self-reported minimal knowledge about, and limited experience with, genetic testing. The main exception was screening for sickle cell trait (SCT) for which most (84%) reported moderate/significant/expert knowledge and over two-thirds had ordered testing. Although most respondents thought it appropriate to counsel and test for health conditions associated with cardiac and connective tissue disorders in the setting of a positive family history, only a minority had been asked to do so. Five or fewer respondents (2%) had been asked to test for performance-associated variants (Angiotensin Converting Enzyme (ACE) II and Alpha-Actinin 3 (ACTN3)), and five or fewer (2%) would recommend changes based on the results. Our study provides a baseline of current US sports medicine physicians’ minimal experiences with, and knowledge of, genetic testing. The findings of our study indicate that sports medicine physicians require further genetics education as it relates to sports and exercise in order to be prepared to competently engage with their patients and to develop sound professional organizational policies.
... Talent is a necessary but in no way sufficient condition for sport success. Sporting development takes place in a highly complex interplay between genetic predispositions and environmental impact (Yan et al. 2016;Mattson et al. 2016). Sport-relevant phenotypes (observable outcomes of the gene-environment interplay in terms of physical or behavioral characteristics with impact on sport performance) range from biochemical and physiological properties such as hematocrit levels in the blood, via appearance characteristics such as size and shape of the body, to complex behavior such as advanced technical and tactical athletic skills. ...
The use of certain performance-enhancing drugs (PED) is banned in sport. I discuss critically standard justifications of the ban based on arguments from two widely used criteria: fairness and harms to health. I argue that these arguments on their own are inadequate, and only make sense within a normative understanding of athletic performance and the value of sport. In the discourse over PED, the distinction between “natural” and “artificial” performance has exerted significant impact. I examine whether the distinction makes sense from a moral point of view. I propose an understanding of “natural” athletic performance by combining biological knowledge of training with an interpretation of the normative structure of sport. I conclude that this understanding can serve as moral justification of the PED ban and enable critical and analytically based line drawing between acceptable and nonacceptable performance-enhancing means in sport.
... It is possible that AGTR2 polymorphisms may be associated with an altered AGTR2 expression (Warnecke et al., 2005); however, the precise effects and mechanisms of the AGTR2 A/C polymorphism still need to be explored further via molecular studies. Furthermore, more functional studies that emphasize detailed athlete phenotyping (e.g., muscle strength and power measurements between different genotypes and/or alleles) will be interesting to further confirm this association (Mattsson, Wheeler, Waggott, Caleshu, & Ashley, 2016). ...
The main purpose of this study was to investigate if the rs11091046 (A>C) polymorphism in AGTR2 gene is associated with athletic status in top-level athletes from Brazil. Since the AGTR2 gene is located on the X chromosome, the case-control association study was done separately for women and men. The female cohort was composed of 205 athletes and 241 non-athletes, and the male cohort was composed of 419 athletes and 490 non-athletes. We did not identify an association between the C-allele and the endurance phenotype. However, power athletes had a higher frequency of the A-allele. In women, A/A genotype was overrepresented in international-level power group compared with non-athletes or international-level endurance athletes (23.2% vs. 16.6% or 8.8%, respectively; p < 0.05). In men, the A-allele frequency observed in power athletes or international-level power athletes was statistically different from that observed in non-athletes (51.6% or 57.8% vs. 40.4%; p < 0.009). Furthermore, men sprinters with the A-allele showed significantly faster personal best times for the 100 m than those with the C-allele (10.56 ± 0.32 s vs. 10.93 ± 0.49 s; p < 0.02). In conclusion, it was found that the AGTR2 A-allele is a candidate genetic marker for top-level power athletes.
... To be considered valid, any genotype association needs to be replicated in samples different from those originally studied to test the initial findings (Chanock et al., 2007). Athletic performance and its various components are a complex and multifactorial phenomenon determined IJSNEM Vol. 27, No. 6, 2017 by interplay of multiple gene variants and multiple nongenetic factors (Mattsson et al., 2016). Although the athletic talent identification and prediction is an exciting possibility, to date there is no evidence to support a genotype-phenotype relationship to predict future athletic success in a given sport (Webborn et al., 2015). ...
Carnosine (β-alanyl-L-histidine), abundantly found in skeletal muscle, plays an important role during exercise, especially for high-intensity contractions. Variability in muscle carnosine content between individuals exists and may also be explained by different genetic bases, although no study has addressed the association of polymorphisms in genes related to carnosine metabolism in athletes. This study aimed to investigate the frequency of single nucleotide polymorphisms (SNPs) in the carnosinase genes (CNDP1 and CNDP2) in a large Brazilian cohort of athletes and non-athletes. Eight SNPs were compared between a representative cohort of elite athletes from Brazil (n=908) and a paired group of non-athletes (n=967). The athletes were stratified into three groups: endurance (n=328), power (n=415) and combat (n=165). The CNDP2 rs6566810 (A/A genotype) is overrepresented in endurance athletes, but only in international-level endurance athletes. Three SNPs (CNDP2 rs3764509, CNDP2-CNDP1 rs2346061 and CNDP1 rs2887) were overrepresented in power athletes compared to non-athletes. Carriers of the minor allele had an increased odds ratio of being a power athlete. For the rs2346061 no significant difference was observed in genotype frequencies between power and combat sports athletes, but for rs2887 the power and combat groups showed an inverse genotype distribution. In conclusion, we found that minor alleles carriers for CNDP2 rs3764509 (G-allele), CNDP2-CNDP1 rs2346061 (C-allele) and CNDP1 rs2887 (A-allele) are more likely to be a power athlete. These polymorphisms may be novel genetic markers for power athletes. Furthermore, these results are suggestive of a distinct CNDP genotype for sporting development.
... In conclusion, while it is widely acknowledged that a favourable genotype combined with suitable training will enhance trainability and sporting performance, to date few (i.e. ACTN3 and ACE) polymorphisms have been associated with an acceptable level of replication with endurance or power athletic performance, and none of these associations are strong enough to predict elite sports performance or trainability [14,23,24]. Currently, there is lack of scientific evidence supporting the predictive values of genetic tests (direct-to-consumer) for prescription of exercise training programmes, or for that matter, talent identification. ...
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.
Despite insufficient evidence to support direct-to-consumer genetic testing in routine clinical care, cardiovascular clinicians increasingly face questions about its utility and interpretation because individuals can purchase these tests directly from laboratories. A burgeoning marketplace offers an expanding array of testing options. In many cases, direct-to-consumer genetic testing advertises information that could inform one’s risk of heritable disease, including insight into having a genetic predisposition to cardiovascular disease or data about gene-drug interactions that could affect response to cardiovascular medications. Navigating clinical questions about direct-to-consumer genetic testing involves understanding the evolution and oversight of the marketplace; the scope of direct-to-consumer genetic testing offerings; and the risks, benefits, and limitations of said testing. In this American Heart Association scientific statement, we summarize the state of the direct-to-consumer genetic testing industry, review types of cardiovascular genetic information that may be included in direct-to-consumer genetic testing, describe approaches to evaluate test quality, and provide resources for clinicians navigating questions about direct-to-consumer genetic testing. If direct-to-consumer genetic test information is used in clinical care, care should be taken to assess the limitations of the test, to contextualize the information specifically to the patient, and to corroborate potentially actionable monogenic findings.
O desempenho físico humano é amplamente complexo com inúmeros mediadores e fatores influenciando tal fenômeno. Com o advento e avanços na genética e biologia molecular foi possível dar um passo à frente em inúmeros campos da Ciência. No entanto, quando se refere à Ciência do Esporte, o avanço está engatinhando a passos mais lentos. Apesar das promessas, ainda não há uma maneira de detectar talentos com base apenas em testes genéticos nem predizer o sucesso de um atleta mirim para se tornar um fenômeno. Além disso, marcadores moleculares baseados em expressão gênica e proteica ainda não permitem a associação completa de tais respostas com o desempenho atlético, ou seja, são necessários mais estudos neste sentido. Esforços mundiais para estabelecer um consórcio nacional integrado, como por exemplo, o MoTrPAC, são algumas das ideias que poderão romper essa barreira e trazer novos insights em Genética e Biologia Molecular do Exercício Físico.
This narrative review explores the relationship between genetics and elite endurance athletes, summarizes the current literature, highlights some novel findings, and provides a physiological basis for understanding the mechanistic effects of genetics in sport. Key genetic markers include ACTN3 R577X (muscle fiber composition), ACE I/D (cardiovascular efficiency), and polymorphisms in PPARA, VEGFA, and ADRB2, influencing energy metabolism, angiogenesis, and cardiovascular function. This review underscores the benefits of a multi-omics approach to better understand the complex interactions between genetic polymorphisms and physiological traits. It also addresses long-standing issues such as small sample sizes in studies and the heterogeneity in heritability estimates influenced by factors like sex. Understanding the mechanistic relationship between genetics and endurance performance can lead to personalized training strategies, injury prevention, and improved health outcomes. Future studies should focus on standardized classification of sports, replication studies involving diverse populations, and establishing solid physiological associations between polymorphisms and endurance traits to advance the field of sports genetics.
There is growing interest among professional athletes and their support staff in utilising genetic testing to enhance sports performance. However, the perceptions of athletes and coaches regarding genetic testing for training purposes remain largely unexplored. To address this gap, the present interview study investigated the perceptions of athletes and coaches towards genetic testing. Sixteen professional cyclists and triathletes (and their five coaches) participated in semi-structured online interviews after having received their genetic test results. The in-depth interviews were video-recorded, transcribed, translated, and analysed using reflexive thematic analysis by two independent researchers in MAXQDA. Positive perceptions were mainly linked to the potential added value of genetic testing for sports, the importance of counselling, and the necessity for further research. Negative perceptions were mainly linked to incorrect interpretations and conclusions, the use of genetic tests for talent selection, the reliability and usability of results, confirmation bias, fear of stigma, privacy concerns, and costs. Overall, there is a positive perception towards genetic testing among athletes and coaches, emphasising its potential to personalise training programmes. Although some participants highlighted the risks and limitations associated with genetic testing, these concerns were less common. It is suggested that counselling should accompany genetic testing to help athletes and coaches comprehend both the limitations and potential benefits of genetic testing.
Running biomechanics are affected by fatiguing or prolonged runs. However, no evidence to date has conclusively linked this effect to running-related injury (RRI) development or performance implications. Previous investigations using subject-specific models in running have demonstrated higher accuracy than group-based models, however, this has been infrequently applied to fatigue. In this study, two experiments were conducted to determine whether subject-specific models outperformed group-based models to classify running biomechanics during non-fatigued and fatigued conditions. In the first experiment, 16 participants performed four treadmill runs at or around the maximal lactate steady state. In the second experiment, nine participants performed five prolonged runs using commercial wearable devices. For each experiment, two segments were extracted from each trial from early and late in the run. For each participant, a random forest model was applied with a leave-one-run-out cross-validation to classify between the early (non-fatigued) and late (fatigued) segments. Additionally, group-based classifiers with a leave-one-subject-out cross validation were constructed. For experiment 1, mean classification accuracies for the single-subject and group-based classifiers were 68.2 ± 8.2% and 57.0 ± 8.9%, respectively. For experiment 2, mean classification accuracies for the single-subject and group-based classifiers were 68.9 ± 17.1% and 61.5 ± 11.7%, respectively. Variable importance rankings were consistent within participants, but these rankings differed from each participant to those of the group. Although the classification accuracies were relatively low, these findings highlight the advantage of subject-specific classifiers to detect changes in running biomechanics with fatigue and indicate the potential of using big data and wearable technology approaches in future research to determine possible connections between biomechanics and RRI.
Introduction: Obesity effects on kidney function. Urinary disorders after exercise are also common, and probably due to transient hemodynamic problems in the glomerular and tubular renal function. The purpose of this research is to investigate the relationship of BMI with proteinuria and hematuria after one session of intense continuous and interval exercise in girls.
Methods: In this quasi-experimental research, 45 hostelry high school girl students with a mean age of 15.18 ± 0.39 years were randomly selected and in three groups of 15, they ran 1600 meters in a continuous and interval manner. Urine test collected before, one and 24 hours after activity. The results were analyzed by SPSS version 16 software and one way ANOVA and Pearson correlation coefficient.
Results: Increased proteinuria was significant one hour (P = 0.002) and 24 hours after activity (P = 0.001) in the continuous group. In the continuous group, the relationship between fat percentage (P=0.017) and body mass index (P=0.001) with protein excretion 24 hours after activity was positive and significant. One hour after activity, protein excretion with fat percentage and Body mass index (BMI) had no significant relationship. Hematuria was also not significant after activity.
Conclusion: Body mass index (BMI) and fat percentage were effective on protein excretion after one session of intense physical activity and had no significant effect on hematuria. Therefore, overweight people were advised to participate in interval exercise to lose weight.
Molecular genetic methods are an integral part of recent medicine. Polymerase chain reaction, Sanger sequencing, next-generation sequencing are widely used in many areas: diagnostics of infectious, inherited, oncological diseases, prenatal screening, study of polymorphisms that increase the risk of developing multifactorial diseases or promoting development physical qualities necessary to achieve success in sports and competitive activity. The growing demand for genotyping raises a number of ethical and social issues affecting the degree of usefulness of genotyping a healthy person and the scientific reliability of the data obtained using direct-to-consumer genetic testing.
The review presents and systematizes the laboratory diagnostic methods used today to study nucleic acids that carry important information about human health and physical qualities.
The past two decades have built on the successes of the Human Genome Project identifying the impact of genetics and genomics on human traits. Given the importance of exercise in the physical and psychological health of individuals across the lifespan, using genomics to understand the impact of genes in the sports medicine field is an emerging field. Given the complexity of the systems involved, high-throughput genomics is required to understand genetic variants, their functions, and ultimately their effect on the body. Consequently, genomic studies have been performed across several domains of sports medicine with varying degrees of success. While the breadth of these is great, they focus largely on the following three areas: 1) performance; 2) injury susceptibility; and 3) sports associated chronic conditions, such as osteoarthritis. Herein, we review literature on genetics and genomics in sports medicine, offer suggestions to bolster existing studies, and suggest ways to ideally impact clinical care.
Genetic testing for health-related purposes is becoming increasingly common in the practice of medicine. Identification of genetic forms of cardiovascular disease, including channelopathies, cardiomyopathies, and aortopathies, is becoming more of an important component of sports cardiology practices. This chapter will review general principles of genetic testing and provide guidance on how genetic testing can help in the detection of inherited cardiovascular disorders that are associated with sudden cardiac death and which have an impact on athletes and decisions regarding sports participation. Medical providers who are provided with genetic data on their patient-athletes must be able to separate properly used and validated genetic information from increasingly popular direct-to-consumer genetic testing products that offer unsupported claims to predict such things as athletic ability, sports performance, and injury risk. The growing market of such genetic tests being advertised directly to the athletic community has led to a 2015 scientific consensus statement warning on the danger of these products to aspiring athletes that can be detrimental to their physical and psychological health. Our role as healthcare providers is to use validated genetic testing practices and data as an added tool promoting the health and safety of athletes.
Although optimizing sleep with the goal of optimizing athletic performance is gaining support among the athletic community, sleep and its disorders remain under-recognized and underappreciated. This is critically important as athletic performance is impaired by the presence of inadequate sleep and untreated sleep disorders. Athletes are uniquely at a higher risk for certain sleep disorders such as obstructive sleep apnea, including those in collision sports where athletes with larger body mass and neck size have a distinct advantage.
Sports hernias are diagnosed in over 80% of athletes presenting with chronic groin pain. The genotype distributions of the examined polymorphisms were studied in 95 football players, all males, using the Copenhagen Hip and Groin Outcome Score (HAGOS) questionnaire. DNA extracted from buccal epithelium. Statistical calculations were performed in the R statistical environment (r-project.org) and Odds ratios (OR) were used to estimate genotype associations. Multifactor dimensionality reduction was used to identify multiple sports hernia susceptibility loci.Two single nucleotide polymorphisms MCT1 rs1049434 and COL1A1 rs1800012 are associated with sports hernias (63% testing accuracy shown by random forest). According to the HAGOS questionnaire outcomes, exercise-related pain, reduced mobility, and range of motion in the groin and thigh are typically associated with sports hernia diagnosis (75% testing accuracy shown by random forest).The combination of genetic research and HAGOS questionnaire helped obtain a sensitivity of 93% for the detection of sports hernia. Active engagement in sport is the most important risk factor for sports hernia, so the identification genes SNP in footballers may contribute to taking timely preventive actions. This study is the first demonstration of an association between sports hernia and COL1A1 rs1800012 genotype. The study discovered a synergistic interaction between the indicated polymorphism and the gene polymorphism MCT1 rs1049434. Further investigations are required to study the association between COL12A1 rs240736 gene SNP and sports hernia.
Genetic variation is responsible for a large amount of the inter-individual performance disparities seen in sport. As such, in the last ten years genetic association studies have become more common; with one of the most frequently researched sports being football. However, the progress and methodological rigour of genetic association research in football is yet to be evaluated. Therefore, the aim of this paper was to identify and evaluate all genetic association studies involving football players and outline where and how future research should be directed. Firstly, a systematic search was conducted in the Pubmed and SPORTDiscus databases, which identified 80 eligible studies. Progression analysis revealed that 103 distinct genes have been investigated across multiple disciplines; however, research has predominately focused on the association of the ACTN3 or ACE gene. Furthermore, 55% of the total studies have been published within the last four years; showcasing that genetic association research in football is increasing at a substantial rate. However, there are several methodological inconsistencies which hinder research implications, such as; inadequate description or omission of ethnicity and on-field positions. Furthermore, there is a limited amount of research on several key areas crucial to footballing performance, in particular; psychological related traits. Moving forward, improved research designs, larger sample sizes, and the utilisation of genome-wide and polygenic profiling approaches are recommended. Finally, we introduce the Football Gene Project, which aims to address several of these limitations and ultimately facilitate greater individualised athlete development within football.
There is a large interindividual variance in the response to training in several phenotypes relevant to physical performance—a complex phenomenon, which is the result of the interaction of numerous intrinsic and extrinsic factors. The relative contribution of genetic or environmental factors to this phenotypic variation has long been a topic of discussion. Although both are undoubtedly critical to performance achievement, accumulated evidence suggests an important relative contribution of genetics. Studies that compare DNA structural variations have suggested that certain gene variants may be involved in the interindividual variance of performance achievement, however, the understanding of the influence of genetics on performance have been challenging due to its complex nature. In the last decades, traditional genetic association studies have had limited success, but more robust methodological approaches have been now introduced in order to better evaluate the potential influence of genetics on performance phenotypes.
Despite numerous attempts to discover genetic variants associated with elite athletic performance, injury predisposition and elite/world-class athletic status, there has been limited progress to date. Past reliance on candidate gene studies predominantly focusing on genotyping a limited number of single nucleotide polymorphisms (SNPs) or the insertion/deletion variants in small, often heterogeneous cohorts have not generated the kind of results that could offer solid opportunities to bridge the gap between basic research in exercise sciences and deliverables in biomedicine. A retrospective view of genetic association studies with complex disease traits indicates that transition to hypothesis-free genome-wide approaches will be more fruitful. In studies of complex disease, it is well recognized that the magnitude of genetic associations is often smaller than initially anticipated and, as such, large sample sizes are required to identify them robustly. Thus, alternative approaches involving large-scale, collaborative efforts, within which high-resolution genome-wide data is generated and interrogated using advanced bioinformatics approaches, are likely necessary for meaningful progress to be made. Accordingly, a symposium was held on the Greek island of Santorini from 14-17th May 2015 to review the main findings in exercise genetics and genomics and to explore promising trends and possibilities. The symposium offered a forum for the development of a position stand. Among the participants, many were involved in ongoing collaborative studies. A consensus emerged among participants that it would be advantageous to bring together all current studies and those recently launched into one new large collaborative initiative, which was subsequently named the Athlome Project Consortium.
The general consensus among sport and exercise genetics researchers is that genetic tests have no role to play in talent identification or the individualised prescription of training to maximise performance. Despite the lack of evidence, recent years have witnessed the rise of an emerging market of direct-to-consumer marketing (DTC) tests that claim to be able to identify children's athletic talents. Targeted consumers include mainly coaches and parents. There is concern among the scientific community that the current level of knowledge is being misrepresented for commercial purposes. There remains a lack of universally accepted guidelines and legislation for DTC testing in relation to all forms of genetic testing and not just for talent identification. There is concern over the lack of clarity of information over which specific genes or variants are being tested and the almost universal lack of appropriate genetic counselling for the interpretation of the genetic data to consumers. Furthermore independent studies have identified issues relating to quality control by DTC laboratories with different results being reported from samples from the same individual. Consequently, in the current state of knowledge, no child or young athlete should be exposed to DTC genetic testing to define or alter training or for talent identification aimed at selecting gifted children or adolescents. Large scale collaborative projects, may help to develop a stronger scientific foundation on these issues in the future.
Humans living at high altitude (>2,500 meters above sea level) have acquired unique abilities to survive the associated extreme environmental conditions, including hypoxia, cold temperature, limited food availability and high levels of free radicals and oxidants. Longterm inhabitants of the most elevated regions of the world have undergone extensive physiological and/or genetic changes, particularly in the regulation of respiration and circulation, when compared to lowland populations. Genome scans have identified candidate genes involved in altitude adaption in the Tibetan Plateau and the Ethiopian highlands, in contrast to populations from the Andes, which have not been as intensively investigated. In the present study, we focused on three indigenous populations from Bolivia: two groups of Andean natives, Aymara and Quechua, and the low-altitude control group of Guarani from the Gran Chaco lowlands. Using pooled samples, we identified a number of SNPs exhibiting large allele frequency differences over 900,000 genotyped SNPs. A region in chromosome 10 (within the cytogenetic bands q22.3 and q23.1) was significantly differentiated between highland and lowland groups. We resequenced ~1.5 Mb surrounding the candidate region and identified strong signals of positive selection in the highland populations. A composite of multiple signals like test localized the signal to FAM213A and a related enhancer; the product of this gene acts as an antioxidant to lower oxidative stress and may help to maintain bone mass. The results suggest that positive selection on the enhancer might increase the expression of this antioxidant, and thereby prevent oxidative damage. In addition, the most significant signal in a relative extended haplotype homozygosity analysis was localized to the SFTPD gene, which encodes a surfactant pulmonary-associated protein involved in normal respiration and innate host defense. Our study thus identifies two novel candidate genes and associated pathways that may be involved in high-altitude adaptation in Andean populations.
Cancers exhibit extensive mutational heterogeneity, and the resulting long-tail phenomenon complicates the discovery of genes and pathways that are significantly mutated in cancer. We perform a pan-cancer analysis of mutated networks in 3,281 samples from 12 cancer types from The Cancer Genome Atlas (TCGA) using HotNet2, a new algorithm to find mutated subnetworks that overcomes the limitations of existing single-gene, pathway and network approaches. We identify 16 significantly mutated subnetworks that comprise well-known cancer signaling pathways as well as subnetworks with less characterized roles in cancer, including cohesin, condensin and others. Many of these subnetworks exhibit co-occurring mutations across samples. These subnetworks contain dozens of genes with rare somatic mutations across multiple cancers; many of these genes have additional evidence supporting a role in cancer. By illuminating these rare combinations of mutations, pan-cancer network analyses provide a roadmap to investigate new diagnostic and therapeutic opportunities across cancer types.
ABSTRACT Regular endurance exercise training induces beneficial functional and health effects in human skeletal muscle. The putative contribution to the training response of the epigenome as a mediator between genes and environment has not been clarified. Here we investigated the contribution of DNA methylation and associated transcriptomic changes in a well-controlled human intervention study. Training effects were mirrored by significant alterations in DNA methylation and gene expression in regions with a homogeneous muscle energetics and remodeling ontology. Moreover, a signature of DNA methylation and gene expression separated the samples based on training and gender. Differential DNA methylation was predominantly observed in enhancers, gene bodies and intergenic regions and less in CpG islands or promoters. We identified transcriptional regulator binding motifs of MRF, MEF2 and ETS proteins in the proximity of the changing sites. A transcriptional network analysis revealed modules harboring distinct ontologies and, interestingly, the overall direction of the changes of methylation within each module was inversely correlated to expression changes. In conclusion, we show that highly consistent and associated modifications in methylation and expression, concordant with observed health-enhancing phenotypic adaptations, are induced by a physiological stimulus.
Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of >10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.
In a 2005 paper that has been accessed more than a million times, John Ioannidis explained why most published research findings were false. Here he revisits the topic, this time to address how to improve matters.
Please see later in the article for the Editors' Summary
Purpose: Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers.
Materials and Methods: We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD) in the Atherosclerosis Risk in Communities (ARIC) cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration.
Results: The addition of a GRS to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC. Results are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor single nucleotide polymorphisms (SNPs) are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider.
Conclusion: The proposed method facilitates the standardized incorporation of a GRS in risk assessment.
We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 newly identified loci. Conditional analyses within loci showed that four loci, including GBA, GAK-DGKQ, SNCA and the HLA region, contain a secondary independent risk variant. In total, we identified and replicated 28 independent risk variants for Parkinson's disease across 24 loci. Although the effect of each individual locus was small, risk profile analysis showed substantial cumulative risk in a comparison of the highest and lowest quintiles of genetic risk (odds ratio (OR) = 3.31, 95% confidence interval (CI) = 2.55-4.30; P = 2 × 10(-16)). We also show six risk loci associated with proximal gene expression or DNA methylation.
Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.
As modern humans migrated out of Africa, they encountered many new environmental conditions, including greater temperature extremes, different pathogens and higher altitudes. These diverse environments are likely to have acted as agents of natural selection and to have led to local adaptations. One of the most celebrated examples in humans is the adaptation of Tibetans to the hypoxic environment of the high-altitude Tibetan plateau. A hypoxia pathway gene, EPAS1, was previously identified as having the most extreme signature of positive selection in Tibetans, and was shown to be associated with differences in haemoglobin concentration at high altitude. Re-sequencing the region around EPAS1 in 40 Tibetan and 40 Han individuals, we find that this gene has a highly unusual haplotype structure that can only be convincingly explained by introgression of DNA from Denisovan or Denisovan-related individuals into humans. Scanning a larger set of worldwide populations, we find that the selected haplotype is only found in Denisovans and in Tibetans, and at very low frequency among Han Chinese. Furthermore, the length of the haplotype, and the fact that it is not found in any other populations, makes it unlikely that the haplotype sharing between Tibetans and Denisovans was caused by incomplete ancestral lineage sorting rather than introgression. Our findings illustrate that admixture with other hominin species has provided genetic variation that helped humans to adapt to new environments.
Many sexual differences are known in human and animals. It is well known that females are superior in longevity, while males in athletic performances. Even though some sexual differences are attributed to the evolutionary tradeoff between survival and reproduction, the aforementioned sex differences are difficult to explain by this tradeoff. Here we show that the evolutionary tradeoff occurs among three components: (1) viability, (2) competitive ability and (3) reproductive effort. The sexual differences in longevity and athletic performances are attributed to the tradeoff between viability (survival) and competitive ability that belongs to the physical makeup of an individual, but not related to the tradeoff between survival and reproduction. This provides a new perspective on sex differences in human and animals: females are superior in longevity and disease recovery, while males are superior in athletic performance.
In large collections of tumor samples, it has been observed that sets of genes that are commonly involved in the same cancer pathways tend not to occur mutated together in the same patient. Such gene sets form mutually exclusive patterns of gene alterations in cancer genomic data. Computational approaches that detect mutually exclusive gene sets, rank and test candidate alteration patterns by rewarding the number of samples the pattern covers and by punishing its impurity, i.e., additional alterations that violate strict mutual exclusivity. However, the extant approaches do not account for possible observation errors. In practice, false negatives and especially false positives can severely bias evaluation and ranking of alteration patterns. To address these limitations, we develop a fully probabilistic, generative model of mutual exclusivity, explicitly taking coverage, impurity, as well as error rates into account, and devise efficient algorithms for parameter estimation and pattern ranking. Based on this model, we derive a statistical test of mutual exclusivity by comparing its likelihood to the null model that assumes independent gene alterations. Using extensive simulations, the new test is shown to be more powerful than a permutation test applied previously. When applied to detect mutual exclusivity patterns in glioblastoma and in pan-cancer data from twelve tumor types, we identify several significant patterns that are biologically relevant, most of which would not be detected by previous approaches. Our statistical modeling framework of mutual exclusivity provides increased flexibility and power to detect cancer pathways from genomic alteration data in the presence of noise. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5.
To integrate heterogeneous and large omics data constitutes not only a conceptual challenge but a practical hurdle in the daily analysis of omics data. With the rise of novel omics technologies and through large-scale consortia projects, biological systems are being further investigated at an unprecedented scale generating heterogeneous and often large data sets. These data-sets encourage researchers to develop novel data integration methodologies. In this introduction we review the definition and characterize current efforts on data integration in the life sciences. We have used a web-survey to assess current research projects on data-integration to tap into the views, needs and challenges as currently perceived by parts of the research community.
Although it has long been proposed that genetic factors contribute to adaptation to high altitude, such factors remain largely unverified. Recent advances in high-throughput sequencing have made it feasible to analyze genome-wide patterns of genetic variation in human populations. Since traditionally such studies surveyed only a small fraction of the genome, interpretation of the results was limited.
We report here the results of the first whole genome resequencing-based analysis identifying genes that likely modulate high altitude adaptation in native Ethiopians residing at 3500 m above sea level on Bale Plateau or Chennek field in Ethiopia. Using cross-population tests of selection, we identify regions with a significant loss of diversity, indicative of a selective sweep. We focus on a 208 kbp gene-rich region on chromosome 19, which is significant in both of the Ethiopian subpopulations sampled. This region contains eight protein-coding genes and spans 135 SNPs. To elucidate its potential role in hypoxia tolerance, we experimentally tested whether individual genes from the region affect hypoxia tolerance in Drosophila. Three genes significantly impact survival rates in low oxygen: cic, an ortholog of human CIC, Hsl, an ortholog of human LIPE, and Paf-AHalpha, an ortholog of human PAFAH1B3.
Our study reveals evolutionarily conserved genes that modulate hypoxia tolerance. In addition, we show that many of our results would likely be unattainable using data from exome sequencing or microarray studies. This highlights the importance of whole genome sequencing for investigating adaptation by natural selection.
Eleven susceptibility loci for late-onset Alzheimer's disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer's disease cases and 37,154 controls. In stage 2, 11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer's disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10(-8)) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.
Whether the integration of genetic/omic technologies in sports contexts will facilitate player success, promote player safety, or spur genetic discrimination depends largely upon the game rules established by those currently designing genomic sports medicine programs. The integration has already begun, but there is not yet a playbook for best practices. Thus far discussions have focused largely on whether the integration would occur and how to prevent the integration from occurring, rather than how it could occur in such a way that maximizes benefits, minimizes risks, and avoids the exacerbation of racial disparities. Previous empirical research has identified members of the personal genomics industry offering sports-related DNA tests, and previous legal research has explored the impact of collective bargaining in professional sports as it relates to the employment protections of the Genetic Information Nondiscrimination Act (GINA). Building upon that research and upon participant observations with specific sports-related DNA tests purchased from four direct-to-consumer companies in 2011 and broader personal genomics (PGx) services, this anthropological, legal, and ethical (ALE) discussion highlights fundamental issues that must be addressed by those developing personal genomic sports medicine programs, either independently or through collaborations with commercial providers. For example, the vulnerability of student-athletes creates a number of issues that require careful, deliberate consideration. More broadly, however, this ALE discussion highlights potential sports-related implications (that ultimately might mitigate or, conversely, exacerbate racial disparities among athletes) of whole exome/genome sequencing conducted by biomedical researchers and clinicians for non-sports purposes. For example, the possibility that exome/genome sequencing of individuals who are considered to be non-patients, asymptomatic, normal, etc. will reveal the presence of variants of unknown significance in any one of the genes associated with hypertrophic cardiomyopathy (HCM), long QT syndrome (LQTS), Marfan's syndrome, and other conditions is not inconsequential, and how this information is reported, interpreted, and used may ultimately prevent the individual from participation in competitive sports. Due to the distribution of genetic diversity that reflects our evolutionary and demographic history (including the discernible effects of restricted gene flow and genetic drift associated with cultural constructs of race) and in recognition of previous policies for "leveling" the playing field in competitive sports based on "natural" athletic abilities, preliminary recommendations are provided to discourage genetic segregation of sports and to develop best practice guidelines for genomic sports medicine programs that will facilitate player success, promote player safety, and avoid genetic discrimination within and beyond the program.
Numerous reports of genetic associations with performance-related phenotypes have been published over the past three decades but there has been limited progress in discovering and characterising the genetic contribution to elite/world-class performance, mainly owing to few coordinated research efforts involving major funding initiatives/consortia and the use primarily of the candidate gene analysis approach. It is timely that exercise genomics research has moved into a new era utilising well-phenotyped, large cohorts and genome-wide technologies-approaches that have begun to elucidate the genetic basis of other complex traits/diseases. This review summarises the most recent and significant findings from sports genetics and explores future trends and possibilities.
The early 21st century has witnessed a steady push by scientists, industry leaders, and government officials to make medicine more personalized. To date, the concept of personalized medicine has referred largely to the field of pharmacogenomics. In contrast, relatively few data exist regarding the application of preventive strategies such as physical exercise in the context of personalized medicine. Within this review, we highlight the extant literature and propose five strategies for scientists that may propel the exercise and sports science fields toward this global goal. Notably, these approaches are in addition to methods to maintain adherence to training - a well-known factor in determining exercise responsiveness. Briefly, these strategies include (1) evaluating participant responses to training at the individual as well as group level; (2) identifying sources of variability in responsiveness to training; (3) optimizing exercise dosing strategies to maximize benefits while minimizing barriers to participation; (4) evaluating the efficacy of multimodal interventions for relevant population subgroups; and (5) increasing the clinical relevance of study populations and outcomes in exercise trials. We look forward to seeing these strategies considered in trials of preventive health interventions such as exercise. Extensive future research in this area is needed for the vision of exercise as a personalized form of medicine to become a reality.
Genetic polymorphism is suggested to be associated with human physical performance. The angiotensin I-converting enzyme insertion/deletion (ACE I/D) polymorphism and the α-actinin-3 gene (ACTN3) R577X polymorphism have been most widely studied for such association analysis. However, the findings are frequently heterogeneous. We aim to summarize the associations of ACE I/D and ACTN3 R577X with sport performance by means of meta-analysis.
We systematically reviewed and quantitatively summarized published studies, until October 31, 2012, on relationship between ACE/ACTN3 genetic polymorphisms and sports performance, respectively.
A total of 366 articles on ACE and 88 articles on ACTN3 were achieved by literature search. A significant association was found for ACE II genotype compared to D allele carriage (DD+ID) with increased possibility of physical performance (OR, 1.23; 95% CI, 1.05-1.45). With respect to sport discipline, the II genotype was found to be associated with performance in endurance athletes (OR, 1.35; 95% CI, 1.17-1.55). On the other hand, no significant association was observed for ACTN3 RR genotype as compared to X allele carriage (XX+RX) (OR, 1.03; 95% CI, 0.92-1.15). However, when restricted the analyses to power events, a significant association was observed (OR, 1.21; 95% CI, 1.03-1.42).
Our results provide more solid evidence for the associations between ACE II genotype and endurance events and between ACTN3 R allele and power events. The findings suggest that the genetic profiles might influence human physical performance.
Diseases such as type 2 diabetes (T2D) result from environmental and genetic factors, and risk varies considerably in the population. T2D-related genetic loci discovered to date explain only a small portion of the T2D heritability. Some heritability may be due to gene–environment interactions. However, documenting these interactions has been difficult due to low availability of concurrent genetic and environmental measures, selection bias, and challenges in controlling for multiple hypothesis testing. Through genome-wide association studies (GWAS), investigators have identified over 90 single nucleotide polymorphisms (SNPs) associated to T2D. Using a method analogous to GWAS [environment-wide association study (EWAS)], we found five environmental factors associated with the disease. By focusing on risk factors that emerge from GWAS and EWAS, it is possible to overcome difficulties in uncovering gene–environment interactions. Using data from the National Health and Nutrition Examination Survey (NHANES), we screened 18 SNPs and 5 serum-based environmental factors for interaction in association to T2D. We controlled for multiple hypotheses using false discovery rate (FDR) and Bonferroni correction and found four interactions with FDR <20 %. The interaction between rs13266634 (SLC30A8) and trans-β-carotene withstood Bonferroni correction (corrected p = 0.006, FDR <1.5 %). The per-risk-allele effect sizes in subjects with low levels of trans-β-carotene were 40 % greater than the marginal effect size [odds ratio (OR) 1.8, 95 % CI 1.3–2.6]. We hypothesize that impaired function driven by rs13266634 increases T2D risk when combined with serum levels of nutrients. Unbiased consideration of environmental and genetic factors may help identify larger and more relevant effect sizes for disease associations.
Electronic supplementary material
The online version of this article (doi:10.1007/s00439-012-1258-z) contains supplementary material, which is available to authorized users.
Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the "Metabochip," a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits.
Aerobic ATP generation by the mitochondrial respiratory oxidative phosphorylation system (OXPHOS) is a vital metabolic process for endurance exercise. Notably, mitochondrial DNA (mtDNA) codifies 13 of the 83 polypeptides implied in the respiratory chain. As such, there is a strong rationale for identifying an association between mtDNA variants and "aerobic" (endurance) exercise phenotypes. The aim of this review is to summarize current knowledge on the association between mtDNA, nuclear genes involved in mitochondriogenesis, and elite endurance athletic status. Several studies in nonathletic people have demonstrated an association between certain mtDNA lineages and aerobic performance, characterized by maximal oxygen uptake (VO2max). Whether mtDNA haplogroups are also associated with the status of being an elite endurance athlete is more controversial, with differences between studies arising from the different ethnic backgrounds of the athletic cohorts (Caucasian of mixed geographic origin, Asiatic, or East African).
Exercise phenotypes have played a key role for ensuring survival over human evolution. We speculated that some genetic variants that influence exercise phenotypes could be associated with exceptional survival (i.e. reaching ≥100 years of age). Owing to its effects on muscle structure/function, a potential candidate is the Arg(R)577Ter(X) polymorphism (rs1815739) in ACTN3, the structural gene encoding the skeletal muscle protein α-actinin-3. We compared the ACTN3 R577X genotype/allele frequencies between the following groups of ethnically-matched (Spanish) individuals: centenarians (cases, n = 64; 57 female; age range: 100-108 years), young healthy controls (n = 283, 67 females, 216 males; 21±2 years), and humans who are at the two end-points of exercise capacity phenotypes, i.e. muscle endurance (50 male professional road cyclists) and muscle power (63 male jumpers/sprinters). Although there were no differences in genotype/allele frequencies between centenarians (RR:28.8%; RX:47.5%; XX:23.7%), and controls (RR:31.8%; RX:49.8%; XX:18.4%) or endurance athletes (RR:28.0%; RX:46%; XX:26.0%), we observed a significantly higher frequency of the X allele (P = 0.019) and XX genotype (P = 0.011) in centenarians compared with power athletes (RR:47.6%; RX:36.5%;XX:15.9%). Notably, the frequency of the null XX (α-actinin-3 deficient) genotype in centenarians was the highest ever reported in non-athletic Caucasian populations. In conclusion, despite there were no significant differences with the younger, control population, overall the ACTN3 genotype of centenarians resembles that of world-class elite endurance athletes and differs from that of elite power athletes. Our preliminary data would suggest a certain 'survival' advantage brought about by α-actinin-3 deficiency and the 'endurance'/oxidative muscle phenotype that is commonly associated with this condition.
The detrimental effects of the winner's curse, including overestimation of the genetic effects of associated variants and underestimation of sufficient sample sizes for replication studies are well-recognized in genome-wide association studies (GWAS). These effects can be expected to worsen as the field moves from GWAS into whole genome sequencing. To date, few studies have reported statistical adjustments to the naive estimates, due to the lack of suitable statistical methods and computational tools. We have developed an efficient genome-wide non-parametric method that explicitly accounts for the threshold, ranking, and allele frequency effects in whole genome scans. Here, we implement the method to provide bias-reduced estimates via bootstrap re-sampling (BR-squared) for association studies of both disease status and quantitative traits, and we report the results of applying BR-squared to GWAS of psoriasis and HbA1c. We observed over 50% reduction in the genetic effect size estimation for many associated SNPs. This translates into a greater than fourfold increase in sample size requirements for successful replication studies, which in part explains some of the apparent failures in replicating the original signals. Our analysis suggests that adjusting for the winner's curse is critical for interpreting findings from whole genome scans and planning replication and meta-GWAS studies, as well as in attempts to translate findings into the clinical setting.
Low cardiorespiratory fitness is a powerful predictor of morbidity and cardiovascular mortality. In 473 sedentary adults, all whites, from 99 families of the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study, the heritability of gains in maximal O(2) uptake (VO(2max)) after exposure to a standardized 20-wk exercise program was estimated at 47%. A genome-wide association study based on 324,611 single-nucleotide polymorphisms (SNPs) was undertaken to identify SNPs associated with improvements in VO(2max) Based on single-SNP analysis, 39 SNPs were associated with the gains with P < 1.5 × 10(-4). Stepwise multiple regression analysis of the 39 SNPs identified a panel of 21 SNPs that accounted for 49% of the variance in VO(2max) trainability. Subjects who carried ≤9 favorable alleles at these 21 SNPs improved their VO(2max) by 221 ml/min, whereas those who carried ≥19 of these alleles gained, on average, 604 ml/min. The strongest association was with rs6552828, located in the acyl-CoA synthase long-chain member 1 (ACSL1) gene, which accounted by itself for ~6% of the training response of VO(2max). The genes nearest to the SNPs that were the strongest predictors were PR domain-containing 1 with ZNF domain (PRDM1); glutamate receptor, ionotropic, N-methyl-D-aspartate 3A (GRIN3A); K(+) channel, voltage gated, subfamily H, member 8 (KCNH8); and zinc finger protein of the cerebellum 4 (ZIC4). The association with the SNP nearest to ZIC4 was replicated in 40- to 65-yr-old, sedentary, overweight, and dyslipidemic subjects trained in Studies of a Targeted Risk Reduction Intervention Through Defined Exercise (STRRIDE; n = 183). Two SNPs were replicated in sedentary obese white women exercise trained in the Dose Response to Exercise (DREW) study (n = 112): rs1956197 near dishevelled associated activator of morphogenesis 1 (DAAM1) and rs17117533 in the vicinity of necdin (NDN). The association of SNPs rs884736 in the calmodulin-binding transcription activator 1 (CAMTA1) locus and rs17581162 ~68 kb upstream from regulator of G protein signaling 18 (RGS18) with the gains in VO(2max) in HERITAGE whites were replicated in HERITAGE blacks (n = 247). These genomic predictors of the response of Vo(2max) to regular exercise provide new targets for the study of the biology of fitness and its adaptation to regular exercise. Large-scale replication studies are warranted.
Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.
Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face recognition and text mining. Recent applications of NMF in bioinformatics have demonstrated its ability to extract meaningful information from high-dimensional data such as gene expression microarrays. Developments in NMF theory and applications have resulted in a variety of algorithms and methods. However, most NMF implementations have been on commercial platforms, while those that are freely available typically require programming skills. This limits their use by the wider research community.
Our objective is to provide the bioinformatics community with an open-source, easy-to-use and unified interface to standard NMF algorithms, as well as with a simple framework to help implement and test new NMF methods. For that purpose, we have developed a package for the R/BioConductor platform. The package ports public code to R, and is structured to enable users to easily modify and/or add algorithms. It includes a number of published NMF algorithms and initialization methods and facilitates the combination of these to produce new NMF strategies. Commonly used benchmark data and visualization methods are provided to help in the comparison and interpretation of the results.
The NMF package helps realize the potential of Nonnegative Matrix Factorization, especially in bioinformatics, providing easy access to methods that have already yielded new insights in many applications. Documentation, source code and sample data are available from CRAN.
By impairing both function and survival, the severe reduction in oxygen availability associated with high-altitude environments is likely to act as an agent of natural selection. We used genomic and candidate gene approaches to search for evidence of such genetic selection. First, a genome-wide allelic differentiation scan (GWADS) comparing indigenous highlanders of the Tibetan Plateau (3,200-3,500 m) with closely related lowland Han revealed a genome-wide significant divergence across eight SNPs located near EPAS1. This gene encodes the transcription factor HIF2alpha, which stimulates production of red blood cells and thus increases the concentration of hemoglobin in blood. Second, in a separate cohort of Tibetans residing at 4,200 m, we identified 31 EPAS1 SNPs in high linkage disequilibrium that correlated significantly with hemoglobin concentration. The sex-adjusted hemoglobin concentration was, on average, 0.8 g/dL lower in the major allele homozygotes compared with the heterozygotes. These findings were replicated in a third cohort of Tibetans residing at 4,300 m. The alleles associating with lower hemoglobin concentrations were correlated with the signal from the GWADS study and were observed at greatly elevated frequencies in the Tibetan cohorts compared with the Han. High hemoglobin concentrations are a cardinal feature of chronic mountain sickness offering one plausible mechanism for selection. Alternatively, as EPAS1 is pleiotropic in its effects, selection may have operated on some other aspect of the phenotype. Whichever of these explanations is correct, the evidence for genetic selection at the EPAS1 locus from the GWADS study is supported by the replicated studies associating function with the allelic variants.
Type 2 Diabetes (T2D) and other chronic diseases are caused by a complex combination of many genetic and environmental factors. Few methods are available to comprehensively associate specific physical environmental factors with disease. We conducted a pilot Environmental-Wide Association Study (EWAS), in which epidemiological data are comprehensively and systematically interpreted in a manner analogous to a Genome Wide Association Study (GWAS).
We performed multiple cross-sectional analyses associating 266 unique environmental factors with clinical status for T2D defined by fasting blood sugar (FBG) concentration > or =126 mg/dL. We utilized available Centers for Disease Control (CDC) National Health and Nutrition Examination Survey (NHANES) cohorts from years 1999 to 2006. Within cohort sample numbers ranged from 503 to 3,318. Logistic regression models were adjusted for age, sex, body mass index (BMI), ethnicity, and an estimate of socioeconomic status (SES). As in GWAS, multiple comparisons were controlled and significant findings were validated with other cohorts. We discovered significant associations for the pesticide-derivative heptachlor epoxide (adjusted OR in three combined cohorts of 1.7 for a 1 SD change in exposure amount; p<0.001), and the vitamin gamma-tocopherol (adjusted OR 1.5; p<0.001). Higher concentrations of polychlorinated biphenyls (PCBs) such as PCB170 (adjusted OR 2.2; p<0.001) were also found. Protective factors associated with T2D included beta-carotenes (adjusted OR 0.6; p<0.001).
Despite difficulty in ascertaining causality, the potential for novel factors of large effect associated with T2D justify the use of EWAS to create hypotheses regarding the broad contribution of the environment to disease. Even in this study based on prior collected epidemiological measures, environmental factors can be found with effect sizes comparable to the best loci yet found by GWAS.
This study aimed to identify human genomic regions that are linked to maximal oxygen uptake (V˙o 2 max ) in sedentary individuals or to the responsiveness ofV˙o 2 max to a standardized endurance training program. The results of a genomic scan based on 289 polymorphic markers covering all 22 pairs of autosomes performed on the Caucasian families of the HERITAGE Family Study are presented. The mean spacing of the markers was 11 cM, and a total of 99 families and 415 pairs of siblings were available for the study.V˙o 2 max in the sedentary state was adjusted for the effects of age, sex, body mass, fat mass, and fat-free mass, whereas theV˙o 2 max response was adjusted for age and baseline level of the phenotype. Two analytic strategies were used: a single-point linkage procedure using all available pairs of siblings (SIBPAL) and a multipoint variance components approach using all the family data (SEGPATH). Results indicate that linkages at P values of 0.01 and better are observed with markers on 4q, 8q, 11p, and 14q forV˙o 2 max before training and with markers on 1p, 2p, 4q, 6p, and 11p for the change inV˙o 2 max in response to a 20-wk standardized endurance training program. These chromosomal regions harbor many genes that may qualify as candidate genes for these quantitative traits. They should be investigated in this and other cohorts.
The overarching goal of exercise genomics is to illuminate exercise biology and behaviour in order to better understand the preventive and therapeutic values of exercise. An ancillary aim is to understand the role of genomic variation in human physical attributes and sports performance. The aim of this report is to briefly comment on the current status of exercise genetics and genomics and to suggest potential improvements to the research agenda and translational activities. First, the genomic features of interest to the biology of exercise are defined. Then, the limit of the current focus on common variants and their implications for exercise genomics is highlighted. The need for a major paradigm shift in exercise genomics research is discussed with an emphasis on study designs and appropriately powered studies as well as on more mechanistic and functional research. Finally, a summary of current practices in translational activities compared with what best practice demands is introduced. One suggestion is that the research portfolio of exercise genomics be composed of a larger fraction of experimental and mechanistic investigations and a smaller fraction of observational studies. It is also recommended that research should shift to unbiased exploration of the genome using all the power of genomics, epigenomics and transcriptomics in combination with large observational but preferably experimental study designs, including Mendelian randomisation. In all cases, emphasis on replications is of paramount importance. This represents an extraordinary challenge that can only be met with large-scale collaborative and multicentre research programmes.
The role of the cancer genetic counselor in the management of patients with cancer is discussed in this article. This includes explaining what a genetic counselor is trained to do and how they are credentialed and licensed. In addition, the article explains who to refer for cancer genetic counseling. Once referred, the article describes what actually happens in a pretest and posttest cancer genetic counseling session. Use of a cancer genetic registry and how it can help in practice is discussed. Finally, several mechanisms for identifying a cancer genetic counselor at one's institution or nearby are outlined.
Considerable evidence has established the link between high levels of physical activity (PA) and all-cause and cardiovascular disease (CVD)-specific mortality. Running is a popular form of vigorous PA that has been associated with better overall survival, but there is debate about the dose-response relationship between running and CVD and all-cause survival. In this review, we specifically reviewed studies published in PubMed since 2000 that included at least 500 runners and 5-year follow-up so as to analyze the relationship between vigorous aerobic PA, specifically running, and major health consequences, especially CVD and all-cause mortality. We also made recommendations on the optimal dose of running associated with protection against CVD and premature mortality, as well as briefly discuss the potential cardiotoxicity of a high dose of aerobic exercise, including running (eg, marathons).
Mutations in the DMD gene result in Duchenne or Becker muscular dystrophy due to absent or altered expression of the dystrophin protein. The more severe Duchenne muscular dystrophy typically presents around ages 2 to 5 with gait disturbance, and historically has led to the loss of ambulation by age 12. It is important for the practicing pediatrician, however, to be aware of other presenting signs, such as delayed motor or cognitive milestones, or elevated serum transaminases. Becker muscular dystrophy is milder, often presenting after age 5, with ambulation frequently preserved past 20 years and sometimes into late decades.
Copyright © 2015 Elsevier Inc. All rights reserved.
This Viewpoint discusses the distinction between personalized and precision medicine and the roles the US initiative can play in addressing unmet needs and remaining challenges.
The announcement by President Obama of a precision medicine initiative created excitement in the medical community. The president referred not to personalized medicine but to “precision medicine,” a term given profile by a recent publication from the National Research Council,¹ in which the authors explain that their use of “precision” was intended to avoid the implication that medications would be synthesized personally for single patients. Rather, they hoped to convey a broader concept that would include precisely tailoring therapies to subcategories of disease, often defined by genomics.
Accounting for gene-environment (GxE) interactions in complex trait association studies can facilitate our understanding of genetic heterogeneity under different environmental exposures, improve the ability to discover susceptible genes that exhibit little marginal effect, provide insight into the biological mechanisms of complex diseases, help to identify high-risk subgroups in the population, and uncover hidden heritability. However, significant GxE interactions can be difficult to find. The sample sizes required for sufficient power to detect association are much larger than those needed for genetic main effects, and interactions are sensitive to misspecification of the main effects model. These issues are exacerbated when working with binary phenotypes and rare variants, which bear less information on association. In this work, we present a similarity-based regression method for evaluating GxE interactions for rare variants with binary traits. The proposed model aggregates the genetic and GxE information across markers using genetic similarity thus increasing the ability to detect GxE signals. The model has a random effects interpretation, which leads to robustness against main effect misspecifications when evaluating GxE interactions. We construct score tests to examine GxE interactions and a computationally efficient EM algorithm to estimate the nuisance variance components. Using simulations and data applications, we show that the proposed method is a flexible and powerful tool to study the GxE effect in common or rare variant studies with binary traits.
Copyright © 2015, The Genetics Society of America.
Human migration Molecular marker mtD-Loop Trend of molecular markers Individual DNA barcode Modern human population Anatomically modern humans are known to have widely migrated throughout history. Different scientific evidences suggest that the entire human population descended from just several thousand African migrants. About 85,000 years ago, the first wave of human migration was out of Africa, that followed the coasts through the Middle East, into Southern Asia via Sri Lanka, and in due course around Indonesia and into Australia. Another wave of migration between 40,000 and 12,000 years ago brought humans northward into Europe. However, the frozen north limited human expansion in Europe, and created a land bridge, "Bering land bridge", connecting Asia with North America about 25,000 years ago. Although fossil data give the most direct information about our past, it has certain anomalies. So, molecular archeologists are now using different molecular markers to trace the "most recent common ancestor" and also the migration pattern of modern humans. In this study, we have studied the trend of molecular markers and also the methodologies implemented in the last decades (2003–2014). From our observation, we can say that D-loop region of mtDNA and Y chromosome based markers are predominant. Nevertheless, mtDNA, especially the D-loop region, has some unique features, which makes it a more effective marker for tracing prehistoric footprints of modern human populations. Although, natural selection should also be taken into account in studying mtDNA based human migration. As per technology is concerned, Sanger sequencing is the major technique that is being used in almost all studies. But, the emergence of different cost-effective-and-easy-to-handle NGS platforms has increased its popularity over Sanger sequencing in studying human migration. © 2014 Published by Elsevier B.V.
Significance testing was developed as an objective method for summarizing statistical evidence for a hypothesis. It has been widely adopted in genetic studies, including genome-wide association studies and, more recently, exome sequencing studies. However, significance testing in both genome-wide and exome-wide studies must adopt stringent significance thresholds to allow multiple testing, and it is useful only when studies have adequate statistical power, which depends on the characteristics of the phenotype and the putative genetic variant, as well as the study design. Here, we review the principles and applications of significance testing and power calculation, including recently proposed gene-based tests for rare variants.
The purpose of this study was to compare values of maximal accumulated oxygen deficit (MAOD; a measure of anaerobic capacity) and peak post-exercise blood lactate concentration ([lactate]; a reflection of glycolytic contribution) in running and cycling, in women and men.
One hundred and nineteen women and 104 men performed an exhaustive treadmill test of ~5 min duration; 106 women and 110 men performed an exhaustive cycle ergometer test of ~5 min duration. Oxygen demands for the exhaustive exercise tests were estimated by extrapolation from steady state VO2 values. For running, an upwardly curvilinear relationship between demand and speed (i.e., with demand a function of speed1.05) was used. For cycling, a linear relationship between demand and work rate was used.
The MAOD was 22% higher (P<0.01) in running than in cycling, and 32% higher (P<0.01) in men than in women. Peak [lactate] was 8% higher (P<0.01) in running, and 23% higher (P<0.01) in men. The VO2max was 10% higher (P<0.01) in running, and 14% higher (P<0.01) in men.
These results indicate that some of the differences between running and cycling, which affect MAOD, do not similarly affect VO2max or peak [lactate]. It is possible that greater lactate removal by the upper body musculature during running permits the greater anaerobic capacity in running, and explains the relatively small difference in blood [lactate] in running compared to cycling.
We previously reported the findings from a genome-wide association study of the response of maximal oxygen uptake (VO2max) to an exercise program. Here we follow up on these results to generate hypotheses on genes, pathways and systems involved in the ability to respond to exercise training. A systems biology approach can help us getting closer to a comprehensive physiological description of what is underlying trainability. The primary material for this exploration was the individual single-nucleotide polymorphism (SNP), SNP-gene mapping, and statistical significance levels. We aimed to generate novel hypotheses through analyses that go beyond statistical association of single-locus markers. This was accomplished through three complementary approaches - (i) building de novo evidence of gene candidacy through informatics-driven literature mining, (ii) aggregating evidence from statistical associations to link variant enrichment in biological pathways to VO2max trainability, and (iii) predicting possible consequences of variants residing in the pathways of interest. We started with candidate gene prioritization followed by pathway analysis focused on over-representation analysis (ORA) and gene-set enrichment analysis (GSEA). Subsequently, leads were followed using in silico analysis of predicted SNP functions. Pathways related to cellular energetics (pantothenate and CoA biosynthesis and PPAR signaling pathways) and immune functions (complement and coagulation cascades) had the highest levels of SNP burden. In particular, long-chain fatty acid transport and fatty acid oxidation genes and sequence variants were found to influence differences in VO2max trainability. Together, these methods allow for the hypothesis-driven ranking and prioritization of genes and pathways for future experimental testing and validation.
In an attempt to associate genetic variation with endurance performance, red cell antigens ABO, MNSs, Rhesus, Duffy, Kell, P and red cell enzymes lactate dehydrogenase (EC: 1.1.1.27), malate dehydrogenase (EC: 1.1.1.37), phosphoglucomutasej (EC: 2.7.5.1) and phosphogluconate dehydrogenase (EC: 1.1.1.44) genetic systems were studied in 79 Caucasian athletes who participated in endurance sports during the 1976 Montreal Olympic Games. Gene frequencies were reported and phenotype frequencies were compared to appropriate reference populations. No significant differences were observed between the athletes and the nonathletic populations of reference. Comparisons of three genetic systems could be made with a sample of athletes from the 1968 Mexico Olympic Games. Phenotype frequencies were identical in the two samples of athletes. The search for genetic variants associated with endurance performance should continue for other genetic systems, particularly in skeletal muscle and other tissues related even more closely to this type of performance.
To determine whether Olympic medallists live longer than the general population.
Retrospective cohort study, with passive follow-up and conditional survival analysis to account for unidentified loss to follow-up.
15 174 Olympic athletes from nine country groups (United States, Germany, Nordic countries, Russia, United Kingdom, France, Italy, Canada, and Australia and New Zealand) who won medals in the Olympic Games held in 1896-2010. Medallists were compared with matched cohorts in the general population (by country, age, sex, and year of birth).
Relative conditional survival.
More medallists than matched controls in the general population were alive 30 years after winning (relative conditional survival 1.08, 95% confidence interval 1.07 to 1.10). Medallists lived an average of 2.8 years longer than controls. Medallists in eight of the nine country groups had a significant survival advantage compared with controls. Gold, silver, and bronze medallists each enjoyed similar sized survival advantages. Medallists in endurance sports and mixed sports had a larger survival advantage over controls at 30 years (1.13, 1.09 to 1.17; 1.11, 1.09 to 1.13) than that of medallists in power sports (1.05, 1.01 to 1.08).
Olympic medallists live longer than the general population, irrespective of country, medal, or sport. This study was not designed to explain this effect, but possible explanations include genetic factors, physical activity, healthy lifestyle, and the wealth and status that come with international sporting glory.
We propose in this paper a unified approach for testing the association between rare variants and phenotypes in sequencing association studies. This approach maximizes power by adaptively using the data to optimally combine the burden test and the nonburden sequence kernel association test (SKAT). Burden tests are more powerful when most variants in a region are causal and the effects are in the same direction, whereas SKAT is more powerful when a large fraction of the variants in a region are noncausal or the effects of causal variants are in different directions. The proposed unified test maintains the power in both scenarios. We show that the unified test corresponds to the optimal test in an extended family of SKAT tests, which we refer to as SKAT-O. The second goal of this paper is to develop a small-sample adjustment procedure for the proposed methods for the correction of conservative type I error rates of SKAT family tests when the trait of interest is dichotomous and the sample size is small. Both small-sample-adjusted SKAT and the optimal unified test (SKAT-O) are computationally efficient and can easily be applied to genome-wide sequencing association studies. We evaluate the finite sample performance of the proposed methods using extensive simulation studies and illustrate their application using the acute-lung-injury exome-sequencing data of the National Heart, Lung, and Blood Institute Exome Sequencing Project.
Newly discovered true (non-null) associations often have inflated effects compared with the true effect sizes. I discuss here the main reasons for this inflation. First, theoretical considerations prove that when true discovery is claimed based on crossing a threshold of statistical significance and the discovery study is underpowered, the observed effects are expected to be inflated. This has been demonstrated in various fields ranging from early stopped clinical trials to genome-wide associations. Second, flexible analyses coupled with selective reporting may inflate the published discovered effects. The vibration ratio (the ratio of the largest vs. smallest effect on the same association approached with different analytic choices) can be very large. Third, effects may be inflated at the stage of interpretation due to diverse conflicts of interest. Discovered effects are not always inflated, and under some circumstances may be deflated-for example, in the setting of late discovery of associations in sequentially accumulated overpowered evidence, in some types of misclassification from measurement error, and in conflicts causing reverse biases. Finally, I discuss potential approaches to this problem. These include being cautious about newly discovered effect sizes, considering some rational down-adjustment, using analytical methods that correct for the anticipated inflation, ignoring the magnitude of the effect (if not necessary), conducting large studies in the discovery phase, using strict protocols for analyses, pursuing complete and transparent reporting of all results, placing emphasis on replication, and being fair with interpretation of results.
Research on humans at high-altitudes contributes to understanding the processes of human adaptation to the environment and evolution. The unique stress at high altitude is hypobaric hypoxia caused by the fall in barometric pressure with increasing altitude and the consequently fewer oxygen molecules in a breath of air, as compared with sea level. The natural experiment of human colonization of high-altitude plateaus on three continents has resulted in two-perhaps three-quantitatively different arterial-oxygen-content phenotypes among indigenous Andean, Tibetan and Ethiopian high-altitude populations. This paper illustrates these contrasting phenotypes by presenting evidence for higher hemoglobin concentration and percent of oxygen saturation of hemoglobin among Andean highlanders as compared with Tibetans at the same altitude and evidence that Ethiopian highlanders do not differ from sea-level in these two traits. Evolutionary processes may have acted differently on the colonizing populations to cause the different patterns of adaptation. Hemoglobin concentration has significant heritability in Andean and Tibetan samples. Oxygen saturation has no heritability in the Andean sample, but does among Tibetans where an autosomal dominant major gene for higher oxygen saturation has been detected. Women estimated with high probability to have high oxygen saturation genotypes have more surviving children than women estimated with high probability to have the low oxygen saturation genotype. These findings suggest the hypothesis that ongoing natural selection is increasing the frequency of the high saturation allele at this major gene locus.
A combination of endurance and strength training is generally used to seek further health benefits or enhanced physical performance in older adults compared with either of the training modes alone. The mean change within a training group, however, may conceal a wide range of individual differences in the responses. The purpose, therefore, was to examine the individual trainability of aerobic capacity and maximal strength, when endurance and strength training are performed separately or concurrently.
For this study, 175 previously untrained volunteers, 89 men and 86 women between the ages of 40 and 67 yr, completed a 21-wk period of either strength training (S) twice a week, endurance training (E) twice a week, combined training (ES) four times per week, or served as controls. Training adaptations were quantified as peak oxygen uptake (VO2peak) in a bicycle ergometer test to exhaustion and maximal isometric bilateral leg extension force (MVC) in a dynamometer.
A large range in training responses, similar to endurance or strength training alone, was also observed with combined endurance and strength training in both ΔVO2peak (from -8% to 42%) and ΔMVC (from -12% to 87%). There were no significant correlations between the training responses in VO2peak and MVC in the E, S, or especially in the ES group, suggesting that the same subjects did not systematically increase both aerobic capacity and maximal strength.
The goal of combined endurance and strength training--increasing both aerobic capacity and maximal strength simultaneously--was only achieved by some of the older subjects. New means are needed to personalize endurance, strength, and especially combined endurance and strength training programs for optimal individual adaptations.