When the body comes under pressure from a variety of stressors on a chronic basis, the immune system can become suppressed. It is at this point that the body is more vulnerable to pathogens to which the individual is exposed. In sport, one typical cause of this could be consistently high training loads, where an individual is not fully recovered. In individual sports, there is a strong argument for regular monitoring of IgA, so close tabs can be kept on how that individual is recovering. This monitoring could be daily or even twice daily (before and after practice) because research shows that although moderate exercise can be an immune booster, intense exercise can have the opposite effect i.e. suppress the immune system. Tracking responses to various workouts or competitions can be useful in gaining an insight in to how an athlete copes or recovers. Other stressor can also have an effect on IgA, such as travel and lifestyle factors such as poor sleep, stress (of an emotional or psychological nature) and in the student athlete, academic load. Significant changes in any of these factors will see changes in the baseline norm established for each individual.
The development of individual profile is essential for the interpretation of data on all SOMA tests. It is usual that a minimum of 5 to 6 tests are required to establish a baseline for any individual athlete. That baseline will of course grow with subsequent testing and the greater your data set the more robust your norms become.
Research has shown that if sIgA levels drop significantly from an individual’s baseline norm then athletes have a one in two chance of an infection in the following two to three weeks (Neville et al., 2008; Dunbar et al., 2013). This is a hard-hitting fact.
In team sports, measurement of sIgA is not required so frequently. A perfectly good monitoring system would test players once or twice a week and again referencing individual norms and deviations from such, to contribute in creating a “readiness to train” index.
The chart shows weekly IgA values plotted with the mean (solid line) and 40% above and below (dashed line). Outliers are easy to identify.
Peaks and Troughs
During monitoring it can be seen that on occasion, IgA levels can spike from individual normal levels. This will be the result of one of two factors. Either the individual is fighting an infection (remember that they can be fighting an infection but may not be symptomatic, for example if a relative or housemate has an infection) or when they become acutely stressed. It is quite common in some countries such as Japan, that sIgA is used as an acute stress marker. This can be seen in studies investigating exam stress. We have also seen spikes in IgA in some (but not all) individuals before important competition.
Analysing a Squad
Once you have developed norms for each athlete you can see readiness to train easily in a squad. In the chart below, each black column represents an athlete’s normal range. The red marks are the values for that day, so it is quick and easy to see who is out of range in a squad.
Salivary alpha-amylase (sAA) has appeared increasingly in the literature as an acute stress biomarker, reflecting sympathetic nervous system activity and differs from cortisol which is slower to respond being a function of HPA-activity. Thus the analyte has been used frequently as a rapid acting acute stress marker in the behavioural sciences. Like cortisol, it is very much viewed as a biomarker reflecting the stress response to exertion, yet some argue that sAA is a more sensitive marker, partly because it is quicker to spike after stressful activity, than the more slowly acting cortisol. sAA has been shown to be an alternative marker to determine anaerobic threshold, but the cost of such measurement, as opposed to the cheaper blood lactate, would leave it as a questionable, option where repeated measurements are taken within the test. However, it does have several possibilities as an acute physiological marker in the sport and exercise environment.
There is a strong argument for the use of sAA response to monitor adaptations to training on a longitudinal basis, because levels are likely to be suppressed in elite athletes during heavy training periods. Logic dictates that the hard training periods are where sympathetic withdrawal of the nervous system is likely to happen during non-functional over-reaching. Research is still in its infancy with regards to such monitoring, but certainly gathering momentum and is the focus of much work at Bond University in Gold Coast, Australia. It could certainly be viewed as the “new kid on the block” as regards stress biomarkers. As such, other uses could be for monitoring stress in military and other stressful environments, such as fire fighters, police forces etc.
We have already demonstrated sAA is useful for the construction of an IgA / Amylase ratio which shows better capability for predicting URTI in a cohort of Premier League academy soccer players (presented at International Society of Exercise Immunology Symposium, Newcastle, NSW, Australia in 2013). The IgA / sAA ratio is becoming a very popular biomarking tool in elite soccer teams in the UK, an elsewhere in Europe, as well as a wide range of sports in Australia.
Cortisol, being a catabolic hormone, is commonly measured in sporting environments when trying to categorise responses to different types of training. The theory being that if cortisol is high, then the body is in a catabolic state and thus readiness to train is impaired. Timing of sampling needs to be controlled and factored into the assessment of data due to the strong circadian pattern. Cortisol is often evaluated in context with an anabolic hormone to give a ratio. In sport the hormone of choice is typically Testosterone and in corporate worlds DHEA is used. There is no clear reason for the choice of each anabolic hormone, after all DHEA is a precursor to testosterone. It is well known that testosterone does tend, in general, to be significantly lower in females than males and the DHEA levels tend to be lower with increasing age.
In sport situations where cortisol is monitored routinely, higher levels would tend to indicate greater catabolic breakdown of muscle with acute fatigue. However, during chronic fatigue there may be a situation where cortisol levels tend to be much lower than normal and thus represent a suppressed state.
The charts here show a trend for cortisol to rise as Training Load becomes more dense in an International Rower, building towards summer competition.
In team sports, the squad will usually be tested once or twice per week, in an attempt to monitor recovery status from competitive games or during intense training periods. With individuals, the testing may become a little more frequent and can even be on a daily basis. It is important to remember that, being a stress hormone, both psychological / emotional factors will affect cortisol values as well as physical factors. Thus there is a requirement of an interdisciplinary approach to data interpretation. Like IgA and other analytes there is no clear reference value to aim for, it is a question of again establishing a baseline and examining relative changes form the baseline established for each individual.
This data below shows a strong correlation between group mean salivary cortisol (using the IgA / Cortisol Dual LFD) and group mean HML Distance (Training Load) through half a Premier League season in soccer players.