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1 Departments of Health, Leisure, and Exercise Science and Biology, Appalachian State University, Boone, North Carolina 28608; and 2 Department of Exercise Science, University of South Carolina, Columbia, South Carolina 29208
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ABSTRACT |
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 TOP
 ABSTRACT
 INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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The influence of
carbohydrate (1 l/h of a 6% carbohydrate beverage), gender, and age on
pro- and anti-inflammatory plasma cytokine and hormone changes was
studied in 98 runners for 1.5 h after two competitive marathon
races. The marathoner runners were randomly assigned to carbohydrate
(C, n = 48) and placebo (P, n = 50)
groups, with beverages administered during the races in a double-blind
fashion using color codes. Plasma glucose was higher and cortisol was
lower in the C than in the P group after the race (P < 0.001). For all subjects combined, plasma levels of interleukin
(IL)-10, IL-1 receptor antagonist (IL-1ra), IL-6, and IL-8 rose
significantly immediately after the race and remained above prerace
levels 1.5 h later. The pattern of change in all cytokines did not
differ significantly between the 12 women and 86 men in the study and
the 23 subjects 
50 yr of age and the 75 subjects <50 yr of age. The
pattern of change in IL-10, IL-1ra, and IL-8, but not IL-6, differed
significantly between the C and the P group, with higher postrace
values measured for IL-10 (109% higher) and IL-1ra (212%) in the P
group and for IL-8 (42%) in the C group. In conclusion, plasma levels
of IL-10, IL-1ra, IL-6, and IL-8 rose strongly in runners after a
competitive marathon, and this was not influenced by age or gender.
Carbohydrate ingestion, however, had a major effect in attenuating
increases in cortisol and two anti-inflammatory cytokines, IL-10 and
IL-1ra.
running; cortisol; catecholamines; carbohydrate; gender; age
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INTRODUCTION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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FOR SEVERAL HOURS SUBSEQUENT to heavy exertion, several components of the innate and adaptive immune system are changed strongly but transiently (16). Various mechanisms explaining the altered immunity have been explored, including hormone-induced trafficking of immune cells and the direct influence of stress hormones, prostaglandin E2, cytokines, and other factors (27-29).
Cytokines are low-molecular-weight proteins and peptides that help
control and mediate interactions among cells involved in immune
responses. Exercise bouts that induce muscle cell injury and high,
sustained metabolic workloads have been hypothesized to cause a
sequential release of the proinflammatory cytokines tumor necrosis
factor-
(TNF-), interleukin (IL)-1
, and IL-6, followed very
closely by anti-inflammatory cytokines such as IL-10 and IL-1 receptor
antagonist (IL-1ra) (4-6, 8-10, 15, 19-24, 27-29). TNF- and IL-1 stimulate the production of
IL-6, which induces the acute-phase response and the production of
IL-1ra. Recent work using muscle biopsy and urine samples has shown
more clearly the intimate link between these cytokines (24,
29). The inflammatory cytokines help regulate a rapid migration
of neutrophils and then, later, monocytes into areas of injured muscle cells and other metabolically active tissues to initiate repair (2). Endurance exercise associated with muscle soreness
(e.g., marathon running) induces a greater inflammatory cytokine
response than modes such as cycling, tennis, or rowing, which are more concentric or intermittent in intensity (10, 18, 19).
Little information is available regarding the influence of age and gender on plasma cytokine changes after heavy and sustained exertion. Although adults of all ages appear to recruit immune cells to the blood compartment in a similar fashion, no one has yet reported on postmarathon cytokine changes in younger and older adult runners (25). A growing number of reports indicate that resting plasma levels of cytokines may be higher in older than in younger adults, but this has not yet been tested in a physically fit population, especially under the stress of exercise (25, 26). With regard to gender, no systematic attempt has been made to compare postexercise cytokine changes in male and female subjects. We have always included a few women in our endurance studies, and although their cytokine data have not differed substantially from those of our male subjects, we have not been able to test this statistically because of small subject numbers (15, 17, 19, 20).
Some attempts have been made through chemical or nutritional means (e.g., indomethacin, glutamine, vitamin C, and carbohydrate supplementation) to attenuate pro- and anti-inflammatory cytokine changes after intensive exercise (16). Carbohydrate, compared with placebo, ingestion has been associated with attenuated hormone and immune responses to intensive, prolonged running and cycling in laboratory settings (15-19). This relationship has not been tested during a competitive marathon race. Hormone and immune measures after a competitive race may differ substantially from those in a laboratory setting, because the exercise intensity is under the control of highly motivated runners (23, 24).
The purpose of this study was to investigate the influence of carbohydrate, gender, and age on cytokine changes in a large group of runners after two competitive marathon races. On the basis of our laboratory studies, we hypothesized that the pattern of change in stress hormones and cytokines would differ between runners ingesting carbohydrate or placebo but not between men and women or younger and older adults.
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METHODS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Subjects. Marathon runners were recruited through a letter of invitation before the 10 April 1999 Charlotte Marathon in Charlotte, NC, and the 8 July 2000 Grandfather Mountain Marathon in Boone, NC. The same research design and procedures were used for both marathon race events, and the data were combined. Male and female runners ranging in age from 21 to 72 yr were accepted into the study if they had run at least one competitive marathon and were willing to adhere to all aspects of the research design, including randomization to the carbohydrate or placebo group. Informed consent was obtained from each subject, and the experimental procedures were in accordance with the policy statements of the institutional review board of Appalachian State University.
Research design. Subjects reported to the Appalachian State University Human Performance Laboratory 2-4 wk before the marathon race events for orientation and measurement of body composition and cardiorespiratory fitness. Basic demographic and training data were obtained through a questionnaire. Runners agreed to avoid the use of large-dose vitamin/mineral supplements (>100% of recommended dietary allowances), herbs, and medications known to affect immune function from the time of orientation until after the race. Runners also agreed to avoid ingesting anti-inflammatory medications on the day before or during the race. During orientation, a dietitian instructed the runners to follow a high-carbohydrate diet, record intake in a food record during the 3 days before the race events, and avoid food or beverages containing calories or caffeine from 9 PM on the previous night.
Body composition was assessed from hydrostatic weighing, and maximal O2 uptake was determined using a graded maximal protocol adapted for runners as described in earlier studies from our group (15, 17). O2 uptake and ventilation were measured using the CPX metabolic system (MedGraphics, St. Paul, MN). Maximal heart rate was measured using a chest heart rate monitor (Polar Electro, Woodbury, NY). On the race days, 102 subjects reported to the start area in a 9-h-fasted state at 5-6 AM. After subjects were in a seated position for 10-15 min, blood samples were collected. Body mass was measured, and a chest heart rate monitor was attached to each runner (Polar Electro). The runners were randomly assigned to carbohydrate or placebo groups, with beverage plastic bottles administered in double-blind fashion using color codes. The beverages were supplied by The Gatorade Sports Science Institute (Barrington, IL) as in earlier studies (10, 15, 17, 19). The carbohydrate and placebo beverages were identical in appearance and taste. The two fluids were identical in sodium (~19.0 meq/l) and potassium (~3.0 eq/l) concentration and pH (~3.0). Each runner ingested 650 ml of beverage ~30 min before the start of the races (7 AM). During the race, runners drank ~1,000 ml of beverage each hour. Research assistants were positioned every 3.2 km to deliver color-coded beverage bottles, which contained 500 ml of fluid, and runners ingested the fluid from two bottles per hour. Runners agreed to avoid all other beverages and food before, during, and 1.5 h after the race. The research assistants also recorded heart rates and ratings of perceived exertion (RPE, 6-20 scale) (3) from each runner every 3.2 km. After the runners crossed the race finish line, blood and saliva samples were collected within 5 min and then again 1.5 h after the race. Body mass was also measured after the race. The subjects drank 650 ml of carbohydrate or placebo beverage during the 1.5-h rest period after the race (no food or other beverage was ingested). A postrace questionnaire verified compliance with all aspects of the research design by each runner.Blood cell counts, hormones, glucose, and lactate.
Blood samples were drawn from an antecubital vein with subjects in the
seated position. Routine complete blood counts were performed by a
clinical hematology laboratory (Lab Corp, Burlington, NC) and provided
leukocyte subset counts, hemoglobin, and hematocrit. Other blood
samples were centrifuged in sodium heparin tubes, and plasma was
divided into aliquots and then stored at 
80°C. Plasma cortisol was
assayed using the competitive solid-phase 125I
radioimmunoassay technique (Diagnostic Products, Los Angeles, CA).
Radioimmunoassay kits were also used to determine plasma concentrations
of insulin and growth hormone according to manufacturer's instructions
(Diagnostic Products). Plasma was analyzed spectrophotometrically for
glucose (before and immediately and 1.5 h after the run)
(11). Lactate was measured from finger-stick blood samples
using a lactate analyzer (model 2300 Stat Plus analyzer, Yellow Springs
Instruments, Yellow Springs, OH). The finger-stick samples were taken
simultaneously with blood sample collection from the antecubital vein.
For plasma epinephrine, blood samples were drawn into chilled tubes
containing EGTA and glutathione (RPN532 Vacutainer tubes, Amersham) and
centrifuged, and the plasma was stored at 80°C until analysis.
Plasma concentrations of epinephrine were determined by
high-performance liquid chromatography with electrochemical detection
(13). Plasma volume changes were estimated using the
method of Dill and Costill (7).
Cytokine measurements.
Total plasma concentrations of IL-1, IL-1ra, IL-2, IL-4, IL-6, IL-8,
IL-10, IL-12, interferon-
(IFN-), and TNF- were determined using quantitative sandwich ELISA kits provided by R & D Systems (Minneapolis, MN). All samples and provided standards were analyzed in
duplicate. A high-sensitivity kit was used for the prerace blood
samples for IL-6. For immediate and 1.5-h postrace samples, serum
samples for IL-1ra were diluted at 1:100. A standard curve was
constructed using standards provided in the kits, and the cytokine
concentrations were determined from the standard curves using linear
regression analysis. The assays were a two-step "sandwich" enzyme
immunoassay in which samples and standards were incubated in a 96-well
microtiter plate coated with polyclonal antibodies for the test
cytokine as the capture antibody. After the appropriate incubation
time, the wells were washed and a second detection antibody conjugated
to alkaline phosphatase (IL-1, IL-6, IL-10) or horseradish
peroxidase (IL-1ra, IL-2, IL-4, IL-6 high sensitivity, IL-8, IL-12,
IFN-, TNF-) was added. The plates were incubated and washed, and
the amount of bound enzyme-labeled detection antibody was measured by
addition of a chromogenic substrate. The plates were then read at the
appropriate wavelength (450-570 nm for IL-1ra, IL-1, IL-2,
IL-4, IL-6, IL-8, IL-10, IL-12, IFN-, and TNF-; 490-650 nm
for IL-6 high sensitivity). The minimum detectable concentrations were
as follows: <22 pg/ml for IL-1ra, <1.0 pg/ml for IL-1, <7.0 pg/ml
for IL-2, <10 pg/ml for IL-4, <0.70 pg/ml for IL-6, <0.094 pg/ml for
IL-6 high sensitivity, <10 pg/ml for IL-8, <3.9 pg/ml for IL-10,
<5.0 pg/ml for IL-12, <8.0 pg/ml for IFN-, and 4.4 pg/ml for
TNF-. Mean coefficients of variation were calculated for each set of
data to determine overall mean and range: 6.27 and 4.32-9.38,
respectively. Plasma concentrations for IL-1, IL-2, IL-4, IL-12,
IFN-, and TNF- remained at low or nondetectable pre- and postrace
levels for the 1999 Charlotte Marathon and were not measured again in
the 2000 Grandfather Mountain Marathon.
Statistical analysis.
Statistical significance was set at P < 0.05, and
values are means ± SE. Carbohydrate and placebo groups were
compared for subject characteristics and race performance measures
using Student's t-tests (Table
1). Leukocyte subset counts, cytokine
measures, and hormone values were analyzed using 2 (carbohydrate and
placebo groups) × 3 (times of measurement) repeated-measures
ANOVA (Tables 2 and
3, Figs.
1-3).
If P 
0.05 for the group ×time interaction, the change
from baseline for the immediate postrace and 1.5-h postrace values was
compared between groups using Student's t-tests. For these
two multiple comparisons across groups, a Bonferroni adjustment was
made, with statistical significance set at P < 0.025. These same statistical procedures were used to compare the pattern of
change in all cytokine measures between genders and subjects divided
into two groups on the basis of age (<50 and 50 yr). Pearson
product-moment correlations were used to test the relationship between
postrace cytokine and hormone measures.
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RESULTS |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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Table 1 lists the subject characteristics for the carbohydrate (n = 48) and placebo (n = 50) groups. Data from the 1999 Charlotte Marathon and 2000 Grandfather Mountain Marathon did not differ significantly and were combined. Ninety-eight of 102 runners, including 12 women, complied with all aspects of the study and finished the marathon races. Data for the male and female runners were combined, because no significant differences were measured for the hormone and immune data reported in this study. The marathon runners in this study were highly experienced and committed to regular training and racing but were still well below elite status. The treadmill test data indicate a high degree of cardiorespiratory fitness for this age group. Carbohydrate intake during the 3 days before the marathon races did not differ significantly between groups and averaged 64.7 ± 0.9% of total energy intake.
Heart rate and RPE data were recorded 12 times throughout the 42.2-km
race events. The mean heart rate for the carbohydrate and placebo
groups did not differ significantly until the last 10 km of the race:
152 ± 2 and 143 ± 2 beats/min (84.5 ± 0.7 and 78.7 ± 1.0% of maximal heart rate), respectively
(P < 0.01). RPE (6-20 Borg scale)
(3) rose significantly in both groups throughout the race
and tended to be lower in the carbohydrate than in the placebo runners
during the last 10 km: 16.1 ± 0.3 and 16.8 ± 0.3, respectively (P = 0.06). Postrace lactate tended to be
higher in the carbohydrate than in the placebo runners: 3.1 ± 1.5 and 2.5 ± 1.0 mmol/l, respectively (P = 0.06).
Race times were slower than the marathoner's personal record time of
the previous year (Table 1) because of the hilly terrain of the
Charlotte and Grandfather Mountain marathon race courses. Race time did
not differ significantly between the carbohydrate and placebo groups
(4.31 ± 0.60 and 4.47 ± 0.70 h, respectively),
but when adjusted for the personal record time of each runner from the
previous year, the race time of the placebo group was 0.68 ± 0.05 h slower than 0.42 ± 0.06 h of the carbohydrate
group (a 15.6-min differential; P = 0.002). The
beverage ingestion goal of 1 l/h of running was nearly met for the
carbohydrate and placebo groups (0.97 ± 0.02 and 0.87 ± 0.02 l/h, respectively), and as a result, plasma volume changes were
slight (0.2 ± 0.2% for each group). Temperature and relative
humidity were measured three times during each race event and averaged
19.1°C (range for both marathons was similar, 17.2-23.4°C) and
0.55 (range 0.45-0.65), respectively.
The pattern of change in plasma glucose, insulin, and growth hormone, but not epinephrine, was significantly different between groups (Table 2). Postrace plasma glucose and insulin levels were significantly lower in the placebo group, and 1.5-h postrace growth hormone levels were significantly higher in the placebo than in the carbohydrate group. The pattern of change in plasma cortisol was significantly different between groups [F(2,190) = 6.68, P = 0.002] and was 37% higher 1.5 h after the race in the placebo than in the carbohydrate runners, despite lower exercise heart rates during the last 10 km. The pattern of change in blood neutrophil and monocyte counts was significantly different between groups, with postrace values significantly higher in the placebo group. The pattern of change in blood lymphocyte counts was not significantly different between groups (P = 0.077), with 1.5-h postrace levels dropping significantly below prerace values for both groups.
For all subjects combined, plasma levels of IL-10 (Fig. 2), IL-1ra
(Fig. 3), IL-6, and IL-8 (Table 3) rose strongly immediately after the
race and were still above prerace levels 1.5 h later. Plasma
concentrations for IL-1 and TNF- rose significantly after the
race, but these changes were of very low magnitude (Table 3). Pre- and
postrace levels for IL-2, IL-4, IL-12, and IFN- were low or
nondetectable for all runners, with no significant change measured
(data not shown). The pattern of change in IL-10, IL-1ra, and IL-8, but
not IL-6, IL-1, and TNF-, differed significantly between
carbohydrate and placebo groups, with higher postrace values measured
for IL-10 (109% higher) and IL-1ra (212%) in placebo runners. Plasma
IL-8 was 42% higher in the carbohydrate than in the placebo runners
1.5 h after the race. The pattern of change in all cytokine
measures listed in Table 3 and Figs. 2 and 3 did not differ
significantly between the 12 women and 86 men in the study, and the 23 subjects 50 yr of age and the 75 subjects <50 yr of age (data not shown).
Postrace plasma glucose was significantly and negatively correlated
with IL-1ra (r = 0.34, P = 0.001) and
IL-10 (r = 0.37, P = 0.001) but not
with IL-6 and IL-8. Postrace plasma cortisol was correlated with IL-10
(r = 0.24, P = 0.026) but not with
IL-1ra, IL-8, and IL-6. Postrace IL-1ra was significantly correlated
with IL-10 (r = 0.52, P < 0.001), but
not with IL-8 and IL-6, and IL-8 was significantly correlated with IL-6
(r = 0.64, P < 0.001). Postrace IL-8
was not significantly correlated with blood neutrophil counts.
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DISCUSSION |
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TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES
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This study explored the influence of carbohydrate, age, and gender
on plasma hormone and cytokine changes in 98 runners after two
competitive marathon races. In accordance with the reports of other
investigators, we found that plasma levels of four cytokines, IL-6,
IL-10, IL-1ra, and IL-8, rose strongly in response to race competition
and remained high 1.5 h later (8, 9, 15, 19, 20, 22-25,
27-29). We found that this pattern of change in plasma cytokine levels did not differ significantly between the men and women
or between younger and older adults competing in the marathon races.
Postrace plasma levels of IL-1, TNF-, IL-2, IL-4, IL-12, and
INF- remained near prerace or at nondetectable levels. These results
are nearly identical to those of Suzuki et al. (28), who
measured these same cytokines in a group of 16 male marathon runners
before and immediately after the Beppu-Oita Mainichi Marathon in Japan.
Running-induced muscle cell metabolic activity and damage appear to be
important triggers of macrophage and neutrophil migration and cytokine
release, although this lacks a clear consensus (2, 5, 21, 22, 24,
27). The low postrace plasma levels of proinflammatory cytokines
such as IL-1 and TNF- may be due to the strong inhibitory effects
of IL-10, IL-1ra, IL-6, and cortisol, which together help prevent an
overly active systemic inflammation (24, 27-29). The
increase in the chemokine IL-8, a strong neutrophil chemotactic and
activation protein, suggests a strong postrace activation of
neutrophils, which we and others have measured in previous studies
(17, 21, 28). Unexpectedly, IL-8 was significantly higher
1.5 h after the race in the carbohydrate group, even though neutrophil counts were higher in the placebo group. This calls into
question the proposed link between postexercise plasma IL-8 levels and
blood neutrophil counts, as evidenced by a lack of statistical
correlation between these variables in our subjects.
Similar to our previous studies during which athletes ran or cycled for 2.5 h at high intensity, compared with placebo ingestion, carbohydrate ingestion was linked to higher plasma glucose and insulin levels and lower plasma cortisol and anti-inflammatory cytokine (IL-10 and IL-1ra) levels in runners after the two competitive marathon races (15, 19). No carbohydrate effect, however, was measured for IL-6, which contrasts with our earlier reports. In the laboratory studies, we tightly equated workload intensity between the carbohydrate and placebo conditions, whereas in the competitive marathon races, runners varied their pace according to how they felt. As a result, the placebo runners significantly reduced their exercise intensity during the last 10 km of the races, which more than likely influenced plasma levels of IL-6, as previously reported by Ostrowski et al. (23). The higher exercise intensity among the carbohydrate runners may have also influenced levels of plasma IL-8 and neutrophil activation (21). In a previous study, we showed that 2 h of intermittent rowing exercise at a moderate intensity was not associated with a significant increase in IL-8 (10).
Carbohydrate ingestion during prolonged exercise may influence the immune system through its effects on blood glucose levels and stress hormone output (12, 14, 16). A reduction in blood glucose levels has been linked to hypothalamic-pituitary-adrenal activation, an increased release of adrenocorticotropic hormone and cortisol, increased plasma growth hormone, decreased insulin, and a variable effect on blood epinephrine levels (12, 14-17). Proinflammatory cytokines also activate the hypothalamus-pituitary-adrenal axis, providing a natural negative-feedback system through the anti-inflammatory actions of cortisol, which inhibit the release of IL-1 and IL-6 from monocytes and macrophages (1, 6, 27, 28). Our failure to show an influence of carbohydrate ingestion on plasma epinephrine levels was probably due to the fact that this hormone is best measured through a catheter during the later stages of exercise, rather than through venipuncture 5 min after a race.
In summary, we found that, in male and female, younger and older
marathon runners, plasma levels of four cytokines, IL-6, IL-10, IL-1ra,
and IL-8, rose strongly in response to race competition and remained
high 1.5 h later. Postrace plasma levels of IL-1, TNF-,
IL-2, IL-4, IL-12, and INF- remained near prerace or at nondetectable levels. In accordance with our laboratory studies of
athletes who ran or cycled for 2.5 h at high intensity, compared with placebo ingestion, carbohydrate ingestion in marathoners during
race competition was linked to higher plasma glucose and insulin levels
and lower plasma cortisol, IL-10, and IL-1ra levels (15, 17,
19). Together these data indicate that carbohydrate compared
with placebo ingestion during prolonged and heavy exertion, such as
marathon race competition, attenuates increases in cortisol and two
cytokines, IL-1ra and IL-10, involved in inflammation inhibitory activities.
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ACKNOWLEDGEMENTS |
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This work was funded by a grant from The Gatorade Sports Science Institute (Quaker Oats, Barrington, IL).
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FOOTNOTES |
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Address for reprint requests and other correspondence: D. C. Nieman, PO Box 32071, Dept. of Health, Leisure, and Exercise Science, Appalachian State University, Boone, NC 28608 (E-mail: niemandc{at}appstate.edu).
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 4 December 2000; accepted in final form 8 February 2001.
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METHODS
RESULTS
DISCUSSION
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