Abstract
tics has long been considered to associate with many exer- cise-related traits and sport performance phenotypes. A genetic basis for elite international marathon running performance exists due to the heritability of endurance-related traits. This has prompted a generation of genomic study to identify marathon suc- cess. The aim of this study was to systematically review the evi- dence of genes, and their polymorphisms, that may play a role in marathon running performance. A search strategy was imple- mented on systematic databases following PRISMA guidelines. Studies were case-control, cohort or genome-wide association de- signs and provided data on the genotypes associated with elite marathon athlete status and/or marathon running performance. The search identified 241 studies, from which, 14 studies were deemed suitable for inclusion. A total of 160 different polymor- phisms in 27 genes were identified in 10,442 participants, of which 2,984 were marathon distance runners. The review identi- fied a possible 16 single nucleotide polymorphisms (SNPs) in 14 genes associated with marathon running performance. While multiple genes and their polymorphisms have been associated with marathon running performance, predicting future marathon success based on genomic data is premature due to the lack of replicated studies. There is limited replication of genotype-phe- notype associations and there is possible publication bias, thus, further studies are required to strengthen our understanding of the genes involved in marathon running. Future research utilising ge- nome-wide technologies in large cohorts is required to elucidate
predicting future marathon success based on genomic data is premature due to the lack of replicated studies. There is limited replication of genotype-phe- notype associations and there is possible publication bias, thus, further studies are required to strengthen our understanding of the genes involved in marathon running. Future research utilising ge- nome-wide technologies in large cohorts is required to elucidate the multiple genetic factors that govern complex endurance-re- lated traits and the impact of epigenetics should be considered. Key words: Genetics, exercise, performance, endurance, geno- type. Introduction Marathon running is predominantly determined by maxi- mal oxygen uptake (V 6O 2 max), lactate threshold, running economy and oxygen uptake kinetics (Joyner and Coyle, 2008). It has been acknowledged that to reach elite-level performance a synergy of physiological and psychological traits, combined with an optimal environment are required (Tucker et al., 2013). Physiological parameters of herita- bility such as V 6O 2 max for endurance performance indicate significant genetic components. For example, Bouchard et al. (1999) demonstrated that the heritability of V 6O 2max falls in the range of 40-50%, indicating such parameters present a considerable genetic influence. In addition, elite marathon runners of Kenyan or Ethiopian descent account for 90 of the top 100 marathon running performances of all time and hold the six previous world records (International Association of Athletics Federations, 2018). Based on this geographical concentration of unparalleled success, asser- tions of a genetic endowment for marathon running perfor- mance have been further amplified (Tuker et al., 2013; Vancini et al., 2014). Therefore, a major focus of sport ge- nomics has been to identify specific genes and their poly- morphisms associated with elite-level performance to fa- cilitate in the identification of future athletic talent (Roth, 2012; Popovski et al., 2016). Specifically, one gene that has been extensively studied due to its associated role in endurance performance is angiotensin I-converting en- zyme (ACE) (Gayagay et al., 1998; Montgomery et al., 1998). The ACE gene functional polymorphism is based on either the presence (insertion [I]) or absence (deletion [d]) of an intron sequence. The insertion (I) allele has been positively associated
2016). Specifically, one gene that has been extensively studied due to its associated role in endurance performance is angiotensin I-converting en- zyme (ACE) (Gayagay et al., 1998; Montgomery et al., 1998). The ACE gene functional polymorphism is based on either the presence (insertion [I]) or absence (deletion [d]) of an intron sequence. The insertion (I) allele has been positively associated with elite endurance running perfor- mance in Caucasians due to lower circulating and tissue ACE activity (Myserson et al., 1999). No significant dif- ferences in the ACE I/deletion (D) genotype were found between Kenyan elite marathon runners and their respec- tive general population (Scott et al., 2005). This ethnic dis- parity led to the contention that the East African running phenomenon is not a genetically mediated one (Wilber & Pitsiladis, 2012). On the contrary, the existing research to date, may be interpreted as evidence for the polygenic na- ture of complex endurance-related traits, due to the basis of researching the broader context of endurance performance, but also highlighting the limitations of a single candidate gene approach (Ahmetov et al., 2016). Furthermore, the use of case-control studies has given rise to inconsistent findings (Drozdovska et al., 2013; Tural et al., 2014), which may be attributed to small sample sizes resulting in insufficient statistical power to demonstrate significant ef- fects of numerous genes each with small contributions (Wang et al., 2013). Where previous studies have been con- ducted on general endurance performance rather than spe- cific to elite marathon running, ensuring sufficient statisti- cal power is a particular challenge in elite-level perfor- mance since elite athletes are by definition, limited to a small number of superior individuals. Therefore, it has been suggested that the impact of these issues can be re- duced by pooling single studies into a meta-analysis (Lopez-Leon et al., 2016). To date, meta-analyses have confirmed the associations of ACE and peroxisome prolif- erator-activated receptor alpha (PPARα) genes with endur- Review article
by pooling single studies into a meta-analysis (Lopez-Leon et al., 2016). To date, meta-analyses have confirmed the associations of ACE and peroxisome prolif- erator-activated receptor alpha (PPARα) genes with endur- Review article
Genes and elite marathon running 560 ance performance (Ma et al., 2013; Lopez-Leon et al., 2016). However, it has been suggested that at least 93 ge- netic markers are associated with elite endurance athletic status (Ahmetov et al., 2016). Yet, to date, no review has identified the genetic markers associated specifically to elite marathon running per se. Therefore, the objectives of the current systematic review were to critically examine the evidence concerning genes that may play a role in the performance of elite-level international marathon athletes, and to provide insight into the predictive utility of genetic testing in identifying future marathon success. This investigation of multiple genes, and their polymorphisms, is advantageous as it allows a more comprehensive picture of genotype-phenotype rela- tionships to emerge, thus improving the future application of genomics as a practical tool in marathon talent identifi- cation. Methods Search strategy A published literature search that investigated the associa- tion between genes and marathon performance was con- ducted up to May 2018 and obtained according to the Pre- ferred Reporting Items for Systematic Reviews and Meta- Analyses (PRISMA) guidelines (Moher et al., 2009). A predetermined search strategy was conducted on system- atic databases for publications indexed in PubMed, SPORTDiscus and Google Scholar using combinations of the following search terms: “genes” OR “genetics” OR “genomics” AND “marathon” OR “endurance” OR “elite performance” in the titles of papers. Additional publica- tions were also considered by cross-referencing. A hand search of the reference lists of articles included in the final analysis that were identified via the database search was conducted, as were the first 20 “related articles” of those included database search articles on PubMed. Study selection All publications retrieved were screened by title and any duplicates or those irrelevant to the research question were removed. Abstracts of the remaining studies were then sim- ilarly screened and 24 studies were selected for full-text assessment against the predetermined inclusion and exclu- sion criteria outlined below. Inclusion and exclusion criteria The present review included case-control, cohort and ge- nome-wide association studies (GWAS). To be included, studies were required to provide data on
to the research question were removed. Abstracts of the remaining studies were then sim- ilarly screened and 24 studies were selected for full-text assessment against the predetermined inclusion and exclu- sion criteria outlined below. Inclusion and exclusion criteria The present review included case-control, cohort and ge- nome-wide association studies (GWAS). To be included, studies were required to provide data on the genotypes as- sociated with elite international marathon athlete status and/or marathon running performance published in peer- review journals. Those studies identified as ‘elite’ were based on participants having been international competi- tors and/or national representatives in the marathon dis- tance as determined by entry standards from the Interna- tional Association of Athletics Federations (IAAF, 2018). There were no restrictions applied regarding the age, gen- der or ethnicity of the participants. Studies were excluded if they were: (i) review articles, congress abstracts, editori- als or other non-original articles; (ii) reported in a language other than English. Overall, 14 studies were included for qualitative synthesis. The study selection process and rea- sons for exclusion are illustrated in Figure 1. Studies were assessed for inclusion by two inde- pendent reviewers, RK and DF, with disagreements re- solved by discussion, and arbitration (HJM) if necessary. The reviewers, RK and DF were not blinded to authors, in- stitutions or journals of publication. If a decision on whether to include or exclude a paper could not be made from the title and abstract, full text was obtained and checked. Data extraction and quality assessment For all selected studies, the following data were extracted: (i) first author name; (ii) publication date; (iii) participant characteristics; (iv) study design; (v) genetic markers measured; (vi) allelic frequencies; and (vii) bias. These outcomes were extracted for the narrative review. Risk of bias assessment The risk of bias of individual studies was assessed using the Cochrane Collaboration’s risk of bias tool (RoB 2.0; Higgins et al., 2016). Studies were given an overall risk of bias grade of either “high”, “some” or “low” calculated from the following five domains: a) sequence generation, b) allocation concealment, c) blinding, d) missing outcome data, e)
of bias assessment The risk of bias of individual studies was assessed using the Cochrane Collaboration’s risk of bias tool (RoB 2.0; Higgins et al., 2016). Studies were given an overall risk of bias grade of either “high”, “some” or “low” calculated from the following five domains: a) sequence generation, b) allocation concealment, c) blinding, d) missing outcome data, e) selective reporting of results. If details for a partic- ular domain were insufficient, the risk of bias was assessed as “unclear”. Assessments were performed independently by two authors (RK and DF) with disagreements resolved by discussion, and arbitration (HJM) if necessary. Compo- nents were assessed independently, as per PRISMA (Moher et al., 2009) and Cochrane collaboration (Higgins et al., 2016) recommendations. Data synthesis Qualitative analysis was carried out on the studies selected focusing on the association between genetic markers, elite marathon athlete status and running performance. A narra- tive review was provided in text and tables to summarise study characteristics. If deemed appropriate, a meta-analy- sis was planned for single nucleotide polymorphisms (SNPs) that had been investigated in at least three studies. However, a meta-analysis was not performed due to the heterogeneity of the study characteristics and SNPs meas- ur ed with very few replication studies. Where data was not available in the full-text, original authors were contacted. Results Summary of studies retrieved The search strategy identified 241 studies, of which, fol- lowing cross-referencing and exclusions, 14 full-text arti- cles were identified and included in the qualitative synthe- sis (see Figure 1). Study characteristics The characteristics of the 14 studies are summarised in Ta- ble 1. A total of 160 different polymorphisms in 27 genes were studied in 10,442 participants, of which 2,984 were marathon distance runners, 6,109 were non-athlete controls
Moir et al. 561 Figure 1. Flow diagram of the phases of study selection during the search process based on PRISMA. or 310 power athletes. Of the 160 polymorphisms, 159 were collectively investigated in two studies (Tsianos et al., 2010; He et al., 2015), where a total of 139 polymorphisms were studied in one paper alone by He et al., (2015). Where, the study investigated 84 polymorphisms in two genes, of which there were no reported associations (He et al., 2015). Only the ACE SNP I/D rs4646994 was investi- gated in three studies (Amir et al., 2007; Ash et al., 2011; Tobina et al., 2010). Thirteen of the studies were case-con- trol or cohort designs with only one applying the new GWAS approach (Ahmetov et al., 2015), although GWAS was not applied to the comparison of the athlete groups with the control groups. While 11 studies discovered at least one endurance-related allele, Ash et al. (2011), Saw- czuk et al. (2013) and Papadimitriou et al. (2018) found no genetic association. Due to the heterogeneity of the study characteristics and SNPs measured with very few replication studies, it was deemed inappropriate to amalgamate the results for a meta-analysis. Therefore, the results in the current review were only analysed qualitatively. Risk of bias within studies The risk of bias of each study is presented in Table 2. Over- all, the majority of studies were considered to have a “low” risk of bias in random sequence generation, allocation con- cealment and blinding. However, “high” risk of bias arose from the domains of missing outcome data in both Döring et al. (2010) and Martinez et al. (2009) for whom addition- ally, an “unclear” risk of bias arose from selective report- ing of results. Two studies were also deemed “unclear” for missing outcome data (Ash et al., 2011; Posthumus et al., 2011) and two “unclear” (Ahmetov et al., 2015; Myerson et al., 1999) for selective reporting of results. Results of individual studies Of the ten studies which compared the distribution of SNPs between elite endurance athletes (marathon runners n= 1,832) with control groups (n= 6,109),
studies were also deemed “unclear” for missing outcome data (Ash et al., 2011; Posthumus et al., 2011) and two “unclear” (Ahmetov et al., 2015; Myerson et al., 1999) for selective reporting of results. Results of individual studies Of the ten studies which compared the distribution of SNPs between elite endurance athletes (marathon runners n= 1,832) with control groups (n= 6,109), eight found a sig- nificant difference between the two groups (Table 3). No- tably, the results for the ACE gene were heterogeneous. For example, while Tobina et al. (2010) found a strong as- sociation between ACE I/D rs4646994 and elite endurance runners (p = 0.001; Table 1), Ash et al. (2011) found no significant association (p = 0.16; Table 1). Of the 16 en- durance-related alleles identified, nuclear factor I A-anti- sense RNA 2 (NFIA-AS2) SNP rs1572312 C displayed the highest frequency among elite endurance athletes (95.5%), however, this study was limited to two elite marathon run- ners (Ahmetov et al., 2015).
Genes and elite marathon running 562 Table 1. Characteristics of studies included (bold indicates gene of int erest). References Participants Study design Genes and SNPs measured Outcome(s) Ahmetov et al., 2015 Russian endurance athletes (n= 219; 2 marathon runners), power athletes (n=230), Russian controls (n=192) and European controls (n=1367) GWAS NFIA-AS2 rs1572312 C/A TSHR rs7144481 T/C RBFOX1 rs7191721 G/A C alleles of NFIA-AS2 rs1572312 and TSHR rs7144481 associated with elite endurance athlete status including marathon runners. Amir et al., 2007 Israeli elite marathon runners (n=79), elite power athletes (n=42) and sedentary controls (n=247) Case- control ACE I/D rs4646994 D allele associated with elite mara- thon athlete status. Ash et al., 2011 Ethiopian elite endurance runners (n=76), demographically matched controls (n=410), controls from general Ethiopian population (n=317), power athletes (n=38) Case- control ACE I/D rs4646994; A22982G rs4363 No association with elite Ethiopian runners. Döring et al., 2010 Caucasian male elite endurance ath- letes (n=316; 39 runners) and Cau- casian male sedentary controls (n=304) Case- control HIF1A Pro582Ser; rs11549465; C/T rs17099207 G/A; rs1951795 C/A; rs11158358 C/G; rs2301113 A/C; rs11549467 G/A Pro582 C allele of rs11549465 and A allele of rs17099207 associated with elite endurance runners. He et al., 2015 Chinese elite endurance runners (n=235) and Chinese controls (n=504) Case- control PPARAGCI α (41 SNPs) PPARAGCI β (43 SNPs) PPRCI1 (4 SNPs); TFAM (3 SNPSs); TFB1M (7 SNPs); TFB2M (3 SNPs); NRF1 (14 SNPs); GABPA (2 SNPs); GABPA (5 SNPs); ERRα (4 SNPs); SIRT1 (7 SNPs) No significant association be- tween proliferator-activated re- ceptor γ (PGC)-related genes and elite endurance running status af- ter adjusting for multiple compari- sons. Martinez et al., 2009 Hispanic marathon runners (n=784; 393 3 rd percentile and 388 lowest 3 rd percentile finishers) Case- control AQP1 rs1049305 C/G C allele associated with elite perfor- mance in Hispanic marathon runners. Myerson et al., 1999 Elite runners (n=91; 79 Caucasian) and British controls (n=1906) Case- control ACE I/D rs1049305 C/G I allele positively associated with elite endurance running performance. Papadimitriou et al., 2018 1,5k, 3k, 5k, and 42k m running times of 698 male and female Cau- casian endurance athletes
C allele associated with elite perfor- mance in Hispanic marathon runners. Myerson et al., 1999 Elite runners (n=91; 79 Caucasian) and British controls (n=1906) Case- control ACE I/D rs1049305 C/G I allele positively associated with elite endurance running performance. Papadimitriou et al., 2018 1,5k, 3k, 5k, and 42k m running times of 698 male and female Cau- casian endurance athletes Cohort ACTN3 R577X ACE I/D No association between ACTN3 or ACE I/D genotype and running perfor- mance at any distance. Posthumus et al., 2011 Caucasian male triathlon (incl. 42.2km run) finishers (n=313) Cohort COL5A1 BstUI RFLP rs12722 T/C T allele associated with faster time to complete running component (42.2km) of triathlon. Sawczuk et al., 2013 Polish elite endurance athletes (n=123; 12 marathon runners) and sedentary controls (n=228) Case- control ADRA2A rs553668 C/T No association with elite endurance athlete status including marathon runners. Stebbings et al., 2018 Male marathon runners (n=141) and recreationally active men (n=137) Cohort TTN rs10497520 TTN gene is associated with shorter skele- tal muscle fascicle length and conveys an advantage for marathon running perfor- mance in trained men. Tobina et al., 2010 Japanese male elite endurance run- ners (n=37) and non-athlete con- trols (n=335) Case- control ACE I/D rs4646994 Frequency of the ACE I/D genotype was lower in elite endurance runners than con- trols. The D allele was associated with faster marathon -running speed. Tsianos et al., 2010 Greek Mount Olympus marathon runners (n=438) Cohort ACTN3 rs1815739 AMPD1 rs17602729 BDKRB2 rs1799722 ADRB2 rs1042713 PPARGC1α rs8192678 PPARα rs4253778; rs6902123 rs1053049; rs2267668 APOE rs7412; rs429358 BDKRB2 rs1799722, ADRB2 rs1042713 and AMPD1 rs17602729 as- sociated with endurance running perfor- mance. Wolfarth et al., 2008 Caucasian male elite endurance athletes (n=316; 39 runners) and sedentary male controls (n=299) Case- control NOS3 Glu298Asp rsl799983 G/T (CA)n repeats; 27-bp repeats 4B/4A 164 bp allele of (CA)n repeats asso- ciated with elite endurance runners. NFIA-AS2, nuclear factor I A- antisense RNA 2; TSHR, thyrotropin receptor precursor; RBFOX1, RNA binding protein fox-1 homolog; ACE, angiotensin- converting enzyme; HIF1A, hypoxia-inducible factor 1-alpha, PPARGC1α, peroxisome proliferator-activated receptor gamma coactivator 1-alpha; PPARGC1β, peroxisome proliferator-activated receptor gamma coactivator 1-beta;
Glu298Asp rsl799983 G/T (CA)n repeats; 27-bp repeats 4B/4A 164 bp allele of (CA)n repeats asso- ciated with elite endurance runners. NFIA-AS2, nuclear factor I A- antisense RNA 2; TSHR, thyrotropin receptor precursor; RBFOX1, RNA binding protein fox-1 homolog; ACE, angiotensin- converting enzyme; HIF1A, hypoxia-inducible factor 1-alpha, PPARGC1α, peroxisome proliferator-activated receptor gamma coactivator 1-alpha; PPARGC1β, peroxisome proliferator-activated receptor gamma coactivator 1-beta; PPRC1, peroxisome proliferator-activated receptor gamma c oactivator-related protein 1; TFAM, mitochondrial transcription factor A; TFB1M, mitochondrial transcription factor B1; TFB2M, mitochondrial transcription factor B2; NRF1, nuclear respiratory factor 1; GABPA, GA-binding protein transcription f actor alpha; GABPB1, GA-binding protein transcription factor beta 1; ERRα, estrogen-related receptor alpha; SIRT1, sirtuin-1; AQP1, aquaporin 1; COL5A1, collagen type V alpha-1; ADRA2A, adrenergic receptor alpha 2A; ACTN3, alpha-actinin-3; AMPD1, adenosine monophosphate deaminase 1; BDKRB2, bradykinin receptor B2; ADRB2, adrenergic receptor beta 2; PPARα, peroxisome proliferator activated receptor alpha; PPARD, peroxisome proliferator activated receptor delta; APOE, apolipoprotein E; NOS3, nitric oxide synthase 3.
Description
The review identifies genes associated with marathon success and highlights the need for further research.