Working title: Gene-expression, high performance and the healthy phenotype - exploring gene signatures in elite athletes
and their potential impact on prospective medical research
Gene Expression gives Insight into Training Response
Exercise and fitness are terms becoming more and more important in our increasingly sedentary society. Fitness is usually described via an individual’s aerobic capacity, defined as maximal oxygen consumption (Vo2max) attainable during maximal or exhaustive exercise. Aerobic capacity differs significantly between the sexes and is responsive to exercise interventions. Normal ranges vary e.g. from 43-52 ml/kg/min in male (age 20-29) and 33-42 ml/kg/min in female (age 20-29) untrained subjects and can be increased up to 62-74 (male) and 47-57 (female) ml/kg/min in elite cyclists (Booth & Roberts, 2008). On the individual level, however, response to training interventions can vary substantially, based on specific genetic differences. Monitoring early response on the gene expression level can thus give insight into an individual’s peculiar health status as well as adaption and mal-adaption to training interventions.
The utility of gene expression for monitoring and predicting training responses requires the identification of robust normative exercise-induced gene expression signatures that are associated with exercise intensity, volume and mode.
Gene expression in whole blood - suitable as a mirror of system wide biology
Liew and collegues (Liew, Ma, Tang, Zheng, & Dempsey, 2006) report expression of 80% of all established human genes (partly known as universal housekeeping- genes, but, interestingly also genes that were thought to be very tissue specific) in whole blood. Further studies go even beyond sole expression and report correlation of detectable gene response in whole blood with occurring physiological changes and pathological states in other body tissues.
As a connective tissue that is distributed throughout the human body, human blood cells seem to be affected by micro- and macro environments and changes of their respective conditions.
A research team at the University of Jena, in Germany, for example reported that gene expression in white blood cells responds to exercise with distinct expression patterns. 450 genes were significantly up- and 150 down- regulated following an exhaustive treadmill test. Several other studies are available.
All of those findings indicate blood as a very accessible matrix with great potential for health-monitoring and physiological research on the transkriptom level.
Exercise Induced Gene Expression
As indicated above, (Büttner, Mosig, Lechtermann, Funke, & Mooren, 2007) demonstrated 450 genes were up-regulated and 150 down-regulated (>1.5-fold change) in human white blood cells following an exhaustive treadmill test at 80% of their maximal o2 uptake with enrichment of genes associated with gene ontology terms such as ‘response to stress’, ‘inflammatory response’ and ‘apoptosis’. The authors generated a list of exercise-induced gene expression, which included 35 up-regulated genes related to stress proteins/stress signalling, extracellular matrix, electrolyte and substrate transport, cytokines, and transcription factors. Interestingly this research team demonstrated that the extent of up- and down-regulation in gene expression was workload dependent and that overall there were remarkable similarities within individuals (suggestive of a specific gene expression pattern induced by exercise), with differences between individuals likely associated with prior training status.
The Importance of Exercise Physiology for Medical Research
Evolutionary medicine indicates that many of our current non-transmittable diseases are related to incompatibility between lifestyles and environments in which humans currently live, and the conditions under which human biology evolved (Booth, Chakravarthy, & Spangenburg, 2002). Exploring exercise induced gene expression and comparing gene expression of highly active elite athletes (representing the phenotype assumable closest related to that of the early, modern human) to that of highly sedentary subjects might thus give adjuvant insight into mechanisms most significant on a medical level.
In general, elite athlete performance requires a unique, healthy phenotype, responding repeatedly to extraordinary demands of physical strain. Adaptations to exercise are widespread and occurring in multiple cell types, tissues, organs and cell-cell communication. Exploring elite athletic performance at the gene expression level might thus give useful insight into molecular mechanisms of the long-term training response and adaption which lead to a certain elite athletic phenotype. Given that the elite athletic physiological status can be viewed as a very extreme on a scale of “health related phenotypes”(as opposed to the extreme sedentary individual) discoveries made within this study might substantially influence and guide future research in the medical field. Recent studies for example, have identified a strong association between indices of athletic performance and optimal health of the general public. Both high aerobic capacity and high skeletal muscle strength are associated with lower mortality. Furthermore, higher aerobic capacity and, often, higher skeletal muscle strength are associated with a lower prevalence of most chronic diseases. Convincing epidemiological evidence exists that physical activity decreases coronary artery disease, type-2-diabetes, hypertension, stroke, breast cancer, colon cancer, osteoporosis and loss of cognitive function or a clustering of risk factors such as the metabolic syndrome. It also appears like that maintenance of aerobic capacity and skeletal muscle strength by lifelong physical activity delays the biological ageing in most organ systems, and delays therefore premature death (Booth & Roberts, 2008).
Establishing Distinct Gene Signatures in Elite Athletes– The Current Project
The purpose of this research project is to gain insight into gene expression and the corresponding physiological response of elite athletes.
Genome wide transcriptional profiling has shown that biological states can be described by up-or down-regulation of distinct clusters of tens of genes. In various cases these so called gene signatures could be related e.g. to a patient’s response to pharmacological treatment or certain states of diseases. Exploring human transcriptoms has proven to be a useful tool exploring various biological mechanisms (Peck et al., 2006). Transcriptional profiles in cells and tissues have been used most extensively and to greatest effect in comparative studies identifying genes that are differentially expressed in response to developmental changes, specific environmental exposures, and disease. In contrast, few studies have focused on “healthy” patterns of gene expression in non-diseased individuals, and still fewer have sought to describe the normal extent of inter- and intra-individual variation in elite athletes. Such information is essential to provide a basis for the comprehensive understanding of normal tissue functions and the impact of genetic and environmental factors –such as for example specific types of training- on these. These data might also be used for the development of more robust designs for clinical intervention studies involving complex gene expression analysis.” (Eady et al., 2005)
It is intended to establish a database containing normative transcriptoms of Australian elite athletes of both sexes and throughout various athletic disciplines.
Such a database has not been established yet and would suit several health- and performance-related (research) purposes. Furthermore it could lead to the establishment of a universal method of detecting illegal substance abuse and other types of doping (such as autologous blood transfusion or gene doping, which are not detectable so far) among highly competitive athletes.
Possible research questions could include the following:
- Which transcripts are notably up or down-regulated in whole blood of highly trained elite athletes? Are there training specific adaptions? What are normative ranges and what is the impact of an athlete’s sex on the candidate gene levels? What is the individual (within-subject) day-to-day variation of certain candidate genes? Are certain gene signatures stable enough to be candidates for a reliable biomarker (e.g. for anti doping purposes)?
- The effect of training, altitude exposure and an athlete’s sex on expression of genes known to change following autologous blood transfusion
- How individual is training response? Can categories of specific whole blood transcriptoms be established for specific training modalities and particular sports?
- What are the effects of short exercise bouts on whole blood / muscle transcriptoms of previously untrained subjects?
- How does the transcriptom respond to specific types of training thought to enhance training performance in endurance athletes (such as training at extreme altitude)? To what extend is the EPO pathway affected?
- (Is the hypoxia pathway affected by prolonged travel by plane?)
- How does the whole blood transcriptom respond to autologous blood-transfusion?
- Is there a correlation between altitude training, gene response and specific physiological response (blood composition)? To what extend is the hypoxia pathway affected?
We have the unique opportunity to investigate samples of more than 100 elite (Olympic athletes, world-cup winners, national representatives) athletes from diverse kind of sports and at different stages of training. Insight into the “extreme”, elite athletic phenotype might lead to findings which might be worth being explored further, e.g. regarding mechanistics and future therapies of several states of diseases more typical for sedentary individuals. Endurance type related training outcomes might prove especially promising in regards to finding a treatment for epidemically spreading diseases in Australia such as obesity, type 2 diabetes or cardio-vascular disease. Furthermore, endurance training-induced pathways interact with immunological response and are indicated to be close to cellular response in hijacked cancer cells, another field that is well worth exploration.
The metabolic phenotype of increased aerobic capacity and strength, obtained throughout endurance trained elite athletes and former sedentary individuals, is closely related to the one that ensured survival and determined gene selection in ancient times, as far as 100000 years ago (Behar et al., 2008). Rapidly decreasing glucose tolerance and insulin sensitivity in detraining elite athletes suggest that health status phenotypes are transient and occur on a continuum.
The lack of research to determine the molecular mechanisms of training and detraining has produced a void in knowledge of the establishment and prevention of disease states of today’s major chronic, non-communicable diseases, all of which are related to (and might be mainly caused by) sedentary living. In the age of “translational medicine’’, important clues for better health can probably be revealed by investigating the potential causal relationships among survival, athletic performance and prevention of most chronic diseases by physical activity (Booth & Roberts, 2008).
Why is this research timely and needed:
Physical activity is a fundamental environmental factor that establishes physiological genomics and can modify genomic expression significantly.
A proper understanding of the genetic (and epigenetic) interplay in the etiology of human elite performance might thus, on the one hand, lead to an improvement of training concepts and methods for competitive sports. Elite athletes undergo high intensity training sessions and are exposed to various stressors. Establishment of exercise induced gene responses may be useful to predict future training adaptions, as well as adverse effects such as excessive fatigue or impaired immune status due to a given training intervention.
On the other hand, the outcome of this study might have important public health implications. Investigation of training induced gene signatures might give useful insight into health related phenotypical characteristics which might lead to further health related research and applications. Knowing the predictors of individual responsiveness to exercise e.g., would be very beneficial in personalized diagnostics and disease management. Revealing cellular mechanisms that underlie response and adaption to exercise might further lead to a better understanding of the mechanistics of epidemiologically spread diseases such as diabetes, coronary heart disease or the metabolic syndrome and thus lead to improvement and optimization of novel therapies.
In addition the establishment of a biomarker specific for autologous blood transfusion might lead to early detection of transgressive blood doping in elite athletes, which might enable early exclusion of affected individuals from competitive sports and support injury prevention.
Timeline and Design
Due to given grants and preexisting research opportunities, I will start the practical part of my research project with the WADA (World Anti Doping Agency) funded AIS ‘normative study’, and look at transkripts known to be most affected by autologous blood transfusion (as established by a previous SIAB project of Simon Easteal and Jennifer Henderson). I will be looking into samples of transfused subjects, athletes training under normal conditions and samples of athletes undergoing altitude training. I intend to focus on individual day-to –day variation in those samples, inter-individual differences and if possible also effects of different modes of training and the athletes’ sex. If possible I will correlate all of those data to their respective blood counts in order to find out to what extend changes in gene expression might rather be due to changes in blood composition than to up-or down regulation of intra cellular pathways. If possible, obtained gene expression-data will be correct for changes in blood composition. This study is undertaken in collaboration with the Australian Institute of Sports (AIS, Canberra), which has provided funding. Blood-samples as well as further physiological data have been collected, RNA has been extracted. RNA samples will be converted into cDNA (via Superscript assay, Invitrogen) and expression of 47 genes, known to be affected by autplogous blood transfusion will be quantified in ~100 samples via a Fluodigm rtPCR array. This will be performed at the BRF facility of the John Curtin School of Medical Research. Obtained data will subsequently be analyzed via statistical packages of the open-source computer program “R”. It is intended to investigate whether certain cluster of genes are significantly different in transfused individuals when compared to altitude trained subjects and athletes training under regular, normoxic conditions.
A second part would consist of RNAseq of whole-blood samples of Australian elite Athletes and the establishment of a respective, accesible database of sequence data. However, funding for that project has yet to be confirmed.
In case funding will not be available I intend to look further into pre-existing gene-expression data which have been established in collaboration with the AIS in a similar context.
A third, and theoretical part, will consist of a review of current literature on whole-blood gene-expression and its suitability as an indicator for physiological and pathological conditions.
Figure 1 - The 2006–2007 human performance and health-related fitness gene map.
The map includes all gene entries and QTL that have shown associations or linkages with exercise-related phenotypes. The chromosomes and their regions are from the Gene Map of the Human Genome Web site hosted by the National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD (http://www.ncbi.nlm.nih.gov/).
Behar, D. M., Villems, R., Soodyall, H., Blue-smith, J., Pereira, L., Metspalu, E., Scozzari, R., et al. (2008). The Dawn of Human Matrilineal Diversity. Journal of Human Genetics, (May), 1130-1140. doi:10.1016/j.ajhg.2008.04.002.
Booth, F. W., & Roberts, C. K. (2008). Linking performance and chronic disease risk: indices of physical performance are surrogates for health. British journal of sports medicine, 42(12), 950-2. doi:10.1136/bjsm.2008.052589
Booth, F. W., Chakravarthy, M. V., & Spangenburg, E. E. (2002). Exercise and gene expression: physiological regulation of the human genome through physical activity. The Journal of Physiology, 543(2), 399-411. doi:10.1113/jphysiol.2002.019265
Büttner, P., Mosig, S., Lechtermann, A., Funke, H., & Mooren, F. C. (2007). Exercise affects the gene expression profiles of human white blood cells. Journal of applied physiology (Bethesda, Md. : 1985), 102(1), 26-36. doi:10.1152/japplphysiol.00066.2006
Eady, J. J., Wortley, G. M., Wormstone, Y. M., Hughes, J. C., Astley, S. B., Foxall, R. J., Doleman, J. F., et al. (2005). Variation in gene expression profiles of peripheral blood mononuclear cells from healthy volunteers. Physiological genomics, 22(3), 402-11. doi:10.1152/physiolgenomics.00080.2005
Liew, C.-C., Ma, J., Tang, H.-C., Zheng, R., & Dempsey, A. a. (2006). The peripheral blood transcriptome dynamically reflects system wide biology: a potential diagnostic tool. The Journal of laboratory and clinical medicine, 147(3), 126-32. doi:10.1016/j.lab.2005.10.005
Peck, D., Crawford, E. D., Ross, K. N., Stegmaier, K., Golub, T. R., & Lamb, J. (2006). A method for high-throughput gene expression signature analysis. Genome biology, 7(7), R61. doi:10.1186/gb-2006-7-7-r61