There are many advantages in measuring changes to immune function in saliva, including the ease of sampling; providing a saliva sample is non-invasive and therefore more acceptable to participants, particularly in nutrition intervention studies where healthy volunteers are often sought. Saliva contains factors that reflect the state of the mucosal immune system; for example changes in levels of salivary S-IgA may indicate changes at other mucosal surfaces [4]. In addition, salivary levels of IgG may also provide a picture of serum levels [256]. However, saliva analysis can also be problematic when investigating immunity; it contains proteases that can degrade the salivary immunoglobulins. Immunoglobulin levels might also be affected by diurnal and monthly variations [256] although more research is needed to determine this.
Collection of saliva samples
When investigating the effects of a nutrition supplement such as BC on levels of salivary S-IgA in participants in their real-life environment, it is necessary to understand the constraints when interpreting the results. There is a lack of agreement on how to control for hydration status in athletes. Blannin et al.,
1998 determined that salivary S-IgA secretion rate or S-IgA/osmolality ratio provided the best means to control for the effects of dehydration on saliva flow in males with mixed fitness levels [238]. Fahlman and Engels, 2005 found that the absolute concentration of S-IgA or IgA secretion rate are the best predictors for URTI risk in American footballers [21]. While Blannin et al., 1998 were not investigating the relationship of salivary S-IgA levels with URTI risk; both groups favoured measuring the secretion rate of salivary S-IgA as a means for controlling for the effect of hydration status.
In practice it is difficult to measure flow rate accurately when collecting whole mixed unstimulated saliva samples. The method used by many researchers [21, 48, 85, 153, 241] requires the participant to drool for a set time e.g. one to four minutes, into a standard container and the volume of saliva produced is measured. It is difficult to time the flow rate accurately if the participant and researcher are not in an area that is private and without interruption. This is a
problem when sampling participants in their normal training or work environment. In addition the imposition of time on the participant may encourage them to drool more than they would normally. The measurement of the degree of change in absolute levels of salivary S-IgA, which does not rely on saliva flow rate, could provide the best indication that there has been an effect of an intervention. Given the variability that can occur in design methodology it is very difficult to compare absolute values of salivary S-IgA levels between studies. It is more appropriate to compare the degree of change in levels in response to an intervention.
The time taken to freeze saliva may be one of the most important factors to optimise IgA concentrations in saliva during sample collection procedures [256]. In a review of various saliva sampling and storage methods, inactivation of the proteolytic enzymes appeared to be key in order to optimise salivary S-IgA levels [256]. It appeared that it was the immediate freezing to -70ºC rather than the collection method itself that had the greatest effect on immunoglobulin levels [256]. In addition, saliva samples were supplied from participants who were asked not to eat or drink in the two hours prior to sampling; the reason for this was not specified. The optimal time to collect a saliva sample after eating and drinking has still not been determined and thirty minutes was chosen in this current study to accommodate the participants.
To help minimise time to freezing, saliva samples were immediately placed on dry ice after collection. Production of saliva varied between participants with some producing the required volume within a minute while others took up to five minutes. The frozen samples were held on dry ice until transported to a -80ºC freezer where they were stored until analysis. This was found to be the simplest and most practical method to use when collecting saliva from participants outside the laboratory environment.
It is also not known if there is a diurnal effect on levels of salivary IgA [256]. Previously, to fit in with the distance runners, saliva samples were collected between 6.15am and 7.00am. In this current study saliva samples were collected from the swimmers prior to their morning training session, between
5.15am and 5.30am. At one of the clubs there were only two volunteers, and it was not possible to collect samples for these two before the morning training session. These athletes provided saliva and blood samples on the nominated days at 4pm prior to their afternoon session. The aim of the study was to investigate changes in levels of salivary S-IgA due to BC supplementation; it was assumed that any diurnal effect would not have impacted on changes in absolute salivary S-IgA values if samples were collected from the participant at the same time of day.
There may be a seasonal effect on saliva flow rate [257], lower saliva flow rates have been observed in the summer perhaps due to a more dehydrated state which would have a concentrating effect on levels of salivary S-IgA [257]. In the previous study, the marathon runners were sampled from January to April, 2002 (summer to autumn), and an increase in salivary S-IgA levels was measured in the BC group. It is unlikely that this was due to a seasonal effect on hydration status. In this current investigation saliva samples were collected from the swimmers and age-matched controls between September and December 2003 (spring to summer). In Study 2 saliva samples were collected from the older adults between April and July 2005 (autumn to winter). There were no increases in levels of salivary S-IgA levels, within any of these cohorts, at the end of the supplementation period compared to baseline. There were also no time-related changes in salivary albumin, plasma albumin or saliva osmolality within any of the cohorts; it seems unlikely therefore that there has been an effect of a change in season on saliva flow rate.
In summary in order to determine whether changes to levels of S-IgA in saliva occurred after BC supplementation the same study protocol was applied to each participant throughout the trial. This included standardising the time of day when the saliva samples were collected, the post-prandial sampling time and the time to freeze the saliva samples.
5.4 Haematological parameters
Various haematological parameters were measured at baseline and at the end of the supplementation period, to determine if there were differences between the BC and placebo groups that may have affected levels of salivary S-IgA and confounded the effect of the supplement.
Iron status may impact on immune function, since iron deficiencies can affect the functioning of many immune cells [147]. Therefore it was important to determine whether there had been a change in iron status in the swimmers due to the increased volume of training (given that they were preparing for the Auckland swimming championships). In this study there were no significant changes within this cohort or the age-matched control cohort (students). There were also no changes for either the swimmers or the student cohorts for any of the other haematological parameters.
Within the older adult cohort there were also no significant changes in iron status. However five of the forty five participants (11%) had plasma ferritin levels above the typical physiological level for this age group. Elevated ferritin levels may be indicative of an impaired iron metabolic condition known as haemochromatosis, which results in excessive iron absorption and can lead to parenchymal damage in the liver, heart and pancreas [258]. Haemochromatosis in most individuals is a genetically predetermined condition, although genetic disposition does not explain all incidences [258]. In this study, while there were no differences in median ferritin levels between the BC and placebo groups; four of the five older adults who had elevated ferritin levels were in the BC group. It is known that iron deficiencies affect lymphocyte proliferation in older adults [147] which could impact on salivary S-IgA levels; however it is not known whether elevated iron stores could also impact on levels of salivary S-IgA. Elevated ferritin levels can be indicative of infection or an inflammatory condition. The C-reactive protein results (a marker of inflammatory conditions) indicated that all participants had levels within normal physiological ranges. It seems the elevated ferritin levels were due to some non-infectious cause. As there were no differences between the BC and
placebo groups for the results for liver function tests it was assumed there were no differences in age-related decline of liver function between the groups; despite some of the participants in the BC group having higher ferritin levels. In future studies of nutrition interventions and mucosal immune function in older adults it would be useful to monitor iron status along with liver function tests at baseline and at the end of the intervention. Alternatively, those with ferritin levels outside the physiological typical levels could be excluded.
In the older adult cohort there were also no significant differences and no changes with time for most of the haematological parameters. This suggested that within this cohort there was a degree of homogeneity between the BC and placebo groups. There was an exception however; there were small but significant increases in the red blood cell count and haemoglobin levels in the BC group but not the placebo group after ten weeks of supplementation compared to levels at baseline (see Section 4.1.1 and Appendix 10.21). All results were within the normal physiological range for this age group. It was not possible to determine whether the increase was due to an effect of BC or if it was simply due to normal physiological variation that may not be significant in a larger sample.
In summary measurement of the various haematological parameters indicated that the BC and placebo groups were similar within each cohort and that the parameters did not change between baseline and the end of the supplementation period. It was important to know that there was no adverse effect of training on iron status which may affect immune function in the swimmers cohort over this period. The small significant increases in some of the parameters in the older adult BC group suggest the safety of BC on immune function should be investigated further in this age group.