Vol.:(0123456789)
Sports Medicine (2019) 49 (Suppl 2):S199–S204 
https://doi.org/10.1007/s40279-019-01164-z
REVIEW ARTICLE
Genetic Approaches for Sports Performance: How Far Away Are We?
Michael J. Joyner1 
Published online: 6 November 2019 
© The Author(s) 2019
Abstract
Humans vary in their ‘natural ability’ related to sports performance. One facet of natural ability reflects so-called intrinsic 
ability or the ability to do well with minimal training. A second facet of natural ability is how rapidly an individual adapts 
to training; this is termed trainability. A third facet is the upper limit achievable after years of prolonged intense training; 
this represents both intrinsic ability and also trainability. There are other features of natural ability to consider, for example 
body size, because some events, sports, or positions favor participants of different sizes. In this context, the physiological 
determinants of elite endurance performance, especially running and cycling, are well known and can be used as a template 
to discuss these general issues. The key determinants of endurance performance include maximal oxygen uptake ( ̇VO2max) , 
the lactate threshold, and running economy (efficiency in the case of cycling or other sports). In this article, I use these physi-
ological determinants to explore what is known about the genetics of endurance performance. My main conclusion is that at 
this time there are very few, if any, obvious relationships between these key physiological determinants of performance and 
DNA sequence variation. Several potential reasons for this lack of relationship will be discussed.
Key Points 
‘Natural ability’ or talent is a widely appreciated feature 
of many elements of sports performance.
The assumption is that key physiological elements of 
talent are embedded in, or explained by, interindividual 
differences in DNA sequence.
At this time, interindividual differences in DNA 
sequence explain only a small fraction of the physiology 
underpinning sports performance.
1 Introduction
Over the past 50 or so years, the key physiological deter-
minants of endurance exercise performance have emerged. 
These include maximal oxygen uptake ( ̇VO2max) , the 
lactate threshold, and efficiency. In the case of distance run-
ning, efficiency is typically referred to as running economy 
because it is difficult to calculate efficiency in a strict engi-
neering context in running humans [1]. By contrast, it is 
much easier for cycling.
Data on these three variables can be modeled to predict 
performance, and there are field tests that incorporate several 
of these variables that are also highly predictive of perfor-
mance. For example, in the early 1990s I took emerging 
evidence that humans run the marathon at a pace similar 
to their running speed at lactate threshold, and calculated a 
theoretical upper limit, at least at that time, for the ‘fastest’ 
potential marathon performance by men [2]. This model also 
reasonably predicted the performance of a given individual. 
Likewise, so-called velocity at ̇VO2max was shown to be 
highly correlated with running performance [3]. This latter 
measure incorporates both ̇VO2max and running economy 
into one metric.
The basic idea underpinning these factors is that they 
interact in a predictable way. ̇VO2max can be seen as the 
upper limit of aerobic capacity, the lactate threshold related 
to the fraction of ̇VO2max that can be sustained for a dura-
tion longer than a few minutes, and efficiency or economy 
related to the actual power output or speed during a race that 
can be generated at a given V̇O2. Additionally, the physi-
ological determinants of ̇VO2max and the lactate threshold 
 * Michael J. Joyner 
 
joyner.michael@mayo.edu
1 
Department of Anesthesiology and Perioperative Medicine, 
Mayo Clinic, Rochester, MN 55905, USA
S200
 
M. J. Joyner 
are well understood. Less is known about the physiological 
determinants of efficiency/economy. The question then is, 
if the physiological determinants of ̇VO2max and the lactate 
threshold are well understood, what is known about the con-
tribution of DNA variation to these factors?
Before I go on, I want to share two sets of assumptions 
related to the physiology behind ̇VO2max and the lactate 
threshold. First, for ̇VO2max , the primary physiological 
determinants under most circumstances in most humans 
are related to maximum cardiac output and stroke volume, 
along with red cell mass or total body hemoglobin [4]. In 
other words, the ability of the heart to pump large quanti-
ties of oxygenated blood to the contracting skeletal muscles 
is absolutely critical. While this is not true in every case 
and in every circumstance, for example chronic obstructive 
pulmonary disease (COPD), where the lungs can become 
limiting, it is true for the vast majority of situations. Second, 
the lactate threshold reflects, in large part, some combina-
tion of skeletal muscle mitochondrial content and function 
in the contracting skeletal muscles and perhaps capillary 
density [5, 6]. Efficiency/economy is much more complex 
and likely sport-specific. It also has an element of the com-
petitive medium that needs to be considered. Examples 
include wind resistance during high-speed cycling versus 
lower-speed running, or water resistance for sports such as 
swimming or rowing [1].
Therefore, with this general perspective as a background, 
I will next try to ask what is known about the genetic con-
tributions to the major physiological determinants of endur-
ance exercise performance. A key question then is what 
constitutes ‘genetic’. One approach is to focus on the herit-
ability of key traits related to athletic performance. These are 
typically statistical arguments based on the correlation of a 
given trait between family members, most notably mono- 
or dizygotic twins. If the correlation between monozygotic 
twins is greater than the correlation between dizygotic twins 
then the interpretation is that this similarity is due primarily 
to greater similarities in the DNA of monozygotic twins than 
dizygotic twins [7]. For ̇VO2max , the heritability can be very 
high for monozygotic twins, consistent with the idea that 
there is a major genetic component to this variable. Twin 
(and other family) studies also indicate that there is a sig-
nificant genetic component to the increase in ̇VO2max seen 
with a few months of fitness-type training [8, 9].
While the observations highlighted above suggest there is 
a strong genetic component to training, specific DNA vari-
ants associated with ̇VO2max and how ̇VO2max responds to 
training have been hard to find. While a number of small 
effect size variants considered in concert seem related to 
the rise in ̇VO2max with training, no variants alone or in 
combination that are clearly linked to canonical biological 
pathways likely to underpin cardiac output and red cell mass 
have been identified [10–13].
The issue of limits of genetic ‘causation’ is also part of a 
general trend in genomic research for complex human traits 
that has accelerated in recent years following the completion 
of the human genome project. In the late 1990s and early 
2000s, it was generally assumed that a limited number of 
gene variants would explain much of the risk of develop-
ing common non-communicable diseases. The idea was that 
once these variants were identified, a host of new approaches 
to diagnosis, prevention, and therapy would emerge. Unfor-
tunately, this vision has not been realized and hundreds of 
gene variants with small effect sizes have been associated 
with complex non-communicable diseases. Importantly, 
their role in the diagnosis, prevention, and therapy for these 
diseases remains obscure. These larger issues related to 
genomics and complex disease-related traits have been dis-
cussed in detail elsewhere [14].
2  Oxygen Transport Cascade
Another way to think about endurance performance is via the 
so-called oxygen transport cascade (Fig. 1). In this cascade, 
the path of oxygen from the air to the tissues is considered. 
Therefore, in addition to cardiac output and red cell mass, 
factors such as the lung, capillaries, and skeletal muscle are 
incorporated into this approach. Using this schematic, it is 
possible to further summarize what is known about DNA-
based explanations for differences in other key steps in the 
oxygen transport cascade.
2.1  The Lung
A number of genome-wide association studies (GWAS) have 
been conducted in an effort to understand the role of DNA 
variants in lung function. The vast majority of these have 
focused on lung volumes, and there is little information on 
diffusing capacity. The take-home message from these stud-
ies is that there are a large number of potential common 
DNA variants that explain a tiny fraction of interindividual 
differences in lung function. Additionally, when so-called 
gene scores (composite values for a number of gene vari-
ants associated with a given phenotype) are constructed, 
lung function values in individuals in the highest quartile 
or quintile versus the lowest quartile or quintile frequently 
differ by only a few percentage points. These differences 
typically account for < 0.1 L of a given lung volume and 
are within the limits of the test–retest validity of spirom-
etry [15]. Thus, there is no reason to believe that DNA vari-
ants explain any major difference in lung function in elite 
athletes, or their extremely high ̇VO2max values. Of note, 
individuals who have spent their entire life at high altitude 
have increased pulmonary diffusing capacity, but this is an 
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Limitations to DNA Sequence Explanations for Sports Performance
adaptive response and is not intrinsic to populations who 
have lived at high altitude for generations [16].
2.2  Cardiac Output and Stroke Volume
After the lung, the next step in the oxygen transport cascade 
is cardiac output. The right ventricle of the heart pumps 
blood through the lungs where it is oxygenated and returned 
to the left side of the heart, which delivers it to the systemic 
circulation. A hallmark of elite endurance performance is 
a high maximum cardiac output driven almost exclusively 
by a very large stroke volume [17]. To date, no DNA vari-
ants have been described that explain the impressive levels 
of stroke volume and cardiac output in elite athletes. Addi-
tionally, no DNA variants have been identified that explain 
why some people’s ̇VO2max , and presumably cardiac out-
put, increases more in response to exercise training than 
another’s. In the late 1990s and early 2000s, it was thought 
that differences in the ACE (angiotensin-converting enzyme) 
genotype might contribute to the high stroke volumes and 
̇VO2max values seen in elite athletes, based on the potential 
for these variants to influence cardiac hypertrophy, but that 
seems unlikely at this time [18]. Additionally, the genetic 
contributions to maximum heart rate also appear physiologi-
cally trivial—only a few beats per minute [19].
2.3  Red Cell Mass
In addition to cardiac output, red cell mass or total body 
hemoglobin are also important physiological determinants 
of ̇VO2max . A high cardiac output that pumps anemic blood 
will not deliver much oxygen to the periphery. Thus, red 
cells and hemoglobin are required, together with a high 
cardiac output, to generate the impressive values seen in 
elite endurance athletes. At this time, there are no obvious 
genetic explanations for the high red cell masses seen in elite 
athletes, and these may be more generally linked to plasma 
volume expansion with exercise via the so-called critometer 
concept; in addition, there are examples of individuals with 
rare variants in their erythropoietin-related systems who 
have both high hematocrits and high values for ̇VO2max 
[20, 21].
2.4  Peripheral Circulation
Once the blood leaves the left ventricle and enters the 
peripheral circulation it is delivered to the tissues. A key 
determinant of ̇VO2max is the ability to generate very high 
skeletal muscle blood flows. It is generally accepted that the 
capacity of skeletal muscle to vasodilate exceeds the ability 
(at least in humans) of the heart to sustain very high levels 
of blood flow in a large mass of active skeletal muscles, 
and also preserve blood pressure [22]. This is known as the 
‘sleeping giant hypothesis’. Additionally, endurance exercise 
training does increase capillary density in the trained skel-
etal muscles, and there are also adaptations at the level of 
the resistance vessels and conducting vessels. As is the case 
for cardiac output and red cell mass, there is no clear DNA 
variant-based explanation for interindividual differences in 
these adaptations, or for the very high level of capillary den-
sity that can be seen in some highly trained individuals. It 
is also interesting to note that pharmacological blockade of 
vascular endothelial growth factor (VEGF) does not elimi-
nate the vascular adaptations in animal models [23]. If at 
least some training-induced adaptations can occur when a 
key pathway is blocked, it seems unlikely that there might 
be a major impact of small effect size gene variants on these 
responses.
2.5  Mitochondrial Density
One of the fundamental adaptations to endurance exercise 
training is the increase in mitochondrial density seen in 
trained skeletal muscle. When this was initially observed 
Fig. 1  Schematic representation of the oxygen transport cascade. The 
features of the steps in the cascade associated with endurance exer-
cise performance are well known, as is how these steps respond to 
training. The intermediate physiology is also well understood (e.g. 
the determinants of cardiac output). However, DNA-based explana-
tions for the variability of key steps in the oxygen transport cascade 
have been hard to identify, and, as a result of physiological redun-
dancy in adaptive responses, it is unclear whether the search for 
DNA-based explanations for the key elements of human performance 
outlined in the text will ever be able to tell a detailed deterministic 
story
S202
 
M. J. Joyner 
by John Holloszy in the mid-1960s, it was a revolution-
ary finding that initiated the era of exercise biochemistry 
[24–26]. Subsequent studies in humans showed that highly 
trained individuals with widely different ̇VO2max values 
have similar levels of mitochondrial adaptations in their 
skeletal muscles [6, 27]. As is the case for VEGF above, 
when knockout animals missing so-called ‘master regula-
tors’ for mitochondrial biogenesis are trained, there are still 
significant mitochondrial adaptations [28]. Again, if at least 
some training-induced adaptations can occur when a key 
pathway is blocked or absent, it seems unlikely that there 
might be a major effect of small effect size gene variants on 
these responses.
While twin studies show that skeletal muscle fiber type 
is highly heritable, there is ongoing discussion about so-
called fiber-type transformation in humans in response to 
prolonged intense training [29–31]. In this context, a study 
in a unique set of identical twins highly divergent for physi-
cal activity over decades showed that muscle fiber type, 
especially for ‘slow twitch’ fibers, may be far more plastic 
than previously demonstrated (see Fig. 2) [32].
3  Limitations and Potential Objections 
to This Perspective
There are a number of potential limitations to the perspec-
tives outlined above. The most obvious is that very large 
cohorts of subjects (perhaps numbering in the hundreds of 
thousands) in conjunction with the phenotypes of interest 
and DNA sequence information are simply not available for 
the key steps in the oxygen transport cascade discussed in 
this review. For this sort of cohort to be a reality, beyond 
a blood test for genotyping, detailed measurements of gas 
exchange at rest and during submaximal and maximal 
exercise would be needed. Measurements of cardiac output 
and red cell mass would also be needed, as would serial 
measurements of blood lactate during graded exercise. Mus-
cle biopsies to assess fiber type, mitochondrial function, and 
capillary density would also be essential. The financial and 
logistical barriers to such a research program seem formi-
dable to say the least.
However, if such a cohort ever did emerge, it seems likely, 
based on the data from other phenotypes, that very large 
numbers of variants with very small effect sizes (relative 
risks of 1.1–1.5 are typically reported) would emerge [33]. 
Additionally, any rare DNA variants found in smaller case-
control-like studies would likely show declining penetrance, 
and thus explain less of the physiology in any larger cohorts 
[34]. Importantly, the extent to which these variants would 
be causally or ‘casually’ associated with the physiological 
phenotype of interest would be uncertain, as would their 
overall explanatory power. To address these limitations in 
the studies of common disease risk, so-called polygenic gene 
scores have been developed [35]. However, the predictive 
utility of these scores is questionable for many complex phe-
notypes (e.g. obesity, diabetes, hypertension), and the overall 
genetic contribution to the phenotype of interest is much less 
than environmental and behavioral influences [36].
A final cautionary note is that for many complex human 
phenotypes, genetic association studies can have reproduc-
ibility issues, and also require diverse ethnic cohorts. The 
classic example of the reproducibility problem comes from 
studies of depression where a recent report found essen-
tially no significant and reproducible genetic associations 
for depression [37].
4  Conclusions
The above discussion of the oxygen transport cascade shows 
that while there is evidence, based on family and twin stud-
ies, for a genetic component of ̇VO2max and its trainability, 
it has been difficult to reconcile these observations with any 
specific large effect size gene variants or combinations of 
small effect size variants linked to key physiological path-
ways as a whole. Similar comments can be made about 
peripheral adaptations in skeletal muscle, and the determi-
nants of efficiency are almost certainly complicated by bio-
mechanical and skill-related factors as much as they are by 
genetic components. For considerations such as body size, 
similar observations can be made, and even in the case of 
ACTN3 variants associated with sprinting or power perfor-
mance, the effect sizes are tiny and there are examples of 
elites with the ‘wrong’ genotype [38, 39]. Additionally, in 
some sports such as swimming, the ACTN3 genotype does 
not clearly segregate in sprinters versus endurance athletes 
[40].
0%
20%
40%
60%
80%
100%
Untrained Twin
Trained Twin
Type I Fiber % Distribuon
Fig. 2  Marked differences in percentage slow-twitch fibers from 
the vastus lateralis of monozygotic twins aged in their mid-50s who 
were highly divergent for physical activity. The active twin had been 
engaged in competitive endurance training and competition for dec-
ades [29]
S203
Limitations to DNA Sequence Explanations for Sports Performance
The obvious question is why? One emerging concept is 
that there are many potential genetic pathways to a given 
phenotype [41]. This concept is consistent with ideas that 
biological redundancy underpins complex multiscale physi-
ological responses and adaptations in humans [42]. From an 
applied perspective, the ideas discussed in this review sug-
gest that talent identification on the basis of DNA testing is 
likely to be of limited value, and that field testing, which is 
essentially a higher order ‘bioassay’, is likely to remain a key 
element of talent identification in both the near and foresee-
able future [43]. While it is possible that more explanatory 
DNA-based associations for complex exercise-related traits 
might emerge if detailed physiological phenotyping of large 
cohorts of humans is performed, there are many limitations 
to this perspective. In this context, the advocates of ever-
bigger Ns should carefully review the limits of this approach 
from studies of other complex phenotypes as they make the 
case for a ‘more is better’ approach to future studies.
Acknowledgements This supplement is supported by the Gatorade 
Sports Science Institute (GSSI). The supplement was guest edited by 
Lawrence L. Spriet, who attended a meeting of the GSSI Expert Panel 
in March 2019 and received honoraria from the GSSI, a division of 
PepsiCo, Inc., for his participation in the meeting. Dr. Spriet received 
no honorarium for guest editing the supplement. Dr. Spriet suggested 
peer reviewers for each paper, which were sent to the Sports Medicine 
Editor-in-Chief for approval, prior to any reviewers being approached. 
Dr. Spriet provided comments on each paper and made an editorial 
decision based on comments from the peer reviewers and the Editor-
in-Chief. Where decisions were uncertain, Dr. Spriet consulted with 
the Editor-in-Chief.
Compliance with Ethical Standards 
Funding This article is based on a presentation by Michael Joyner to 
the GSSI Expert Panel in March 2019. Funding for attendance at that 
meeting, together with an honorarium for preparation of this article, 
were provided by the GSSI.
Conflict of interest Michael Joyner has no conflicts of interest relevant 
to the content of this article.
Open Access This article is distributed under the terms of the Crea-
tive Commons Attribution 4.0 International License (http://creat iveco 
mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribu-
tion, and reproduction in any medium, provided you give appropriate 
credit to the original author(s) and the source, provide a link to the 
Creative Commons license, and indicate if changes were made.
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Genetic Approaches for Sports Performance: How Far Away Are We?
Joyner, Michael J