chronic glutamine supplementation increases nasal but not salivary iga during nine days of interval...

7/29/2019 Chronic Glutamine Supplementation Increases Nasal but Not Salivary Iga During Nine Days of Interval Training

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CHRONIC GLUTAMINE SUPPLEMENTATION INCREASES NASAL BUT NOT

SALIVARY IgA DURING NINE DAYS OF INTERVAL TRAINING

Krieger, James W.1, Crowe, Michelle1, and Blank, Sally E.1

1Clinical and Experimental Exercise Science Graduate Program, Washington State

University Spokane, Spokane, WA, 99202-1495

Running Head: CHRONIC GLUTAMINE SUPPLEMENTATION AND NASAL IgA

Contact Information:

James Krieger

Department of Food Science and Human Nutrition

University of Florida

P.O. Box 110370

359 FSHN Building

Newell Drive

Gainesville, FL 32611-0370

Phone: (352) 359-1236

Fax: (352) 392-9467

[email protected]

Articles in PresS. J Appl Physiol (April 23, 2004). 10.1152/japplphysiol.00971.2003

Copyright 2004 by the American Physiological Society.


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ABSTRACT

Oral glutamine supplementation during and after exercise abolishes exercise-induced

decreases in plasma glutamine concentration but does not affect secretory IgA (sIgA)

salivary output. Whether chronic glutamine supplementation during high intensity interval

training influences salivary and nasal sIgA concentration is unknown. PURPOSE: To

examine the effects of chronic glutamine supplementation on sIgA during intense running

training. METHODS: Runners (n= 13, body mass 69.9 2.8 kg, VO2 peak 55.5 2

mL.kg-1min-1, age 29.1 2.8 yr.) participated in twice-daily interval training for 9-9.5 days,

followed by recovery (5-7 days). Oral glutamine supplement (0.1 g

.

kg

-1

) or placebo was

given four times daily for the first 14 days. After an overnight fast, venous blood, nasal

washes, and stimulated saliva were collected at baseline (T1), mid-training (T2), post

training (T3), and after recovery (T4). Mood states were assessed using Profile of Mood

States (POMS) inventories. RESULTS: Glutamine concentration in resting subjects

decreased from T1 to T4 (p


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INTRODUCTION

Epidemiological and anecdotal evidence suggest that athletes engaged in high

volume and/or high intensity training are at an increased risk for upper respiratory tract

infections (URTI) compared to athletes engaged in more moderate forms of training (21).

The mechanisms behind these clinical manifestations are not clear but may result from

training-related changes in immune indices including decreased salivary IgA concentration

and secretion rates (12, 22-24, 35, 36).

Newsholme (29) proposed that decreased availability of glutamine to immune cells

may be a key factor behind some of the changes in an athletes immune system. Glutamine

is an important fuel for immune cells and intestinal mucosal cells (38). Lymphocytes and

macrophages utilize glutamine at high rates and are dependent upon glutamine for

replication (29). Clinical evidence also exists for improved immune indices and reduced

infection rates when glutamine supplementation is provided to trauma, cancer, and post-

operative patients with low plasma glutamine concentration (8). Although physical

training does not typically predispose athletes to extensive periods of reduced plasma

glutamine concentration as observed in clinical populations, Newsholme (29) postulated

that when plasma glutamine concentration decreases below a physiologically normal range

of 0.5-0.9 mM (3), limited glutamine availability may impair certain immune cell

functions, and, in turn, increase an individuals susceptibility to infections, such as URTI.

Plasma glutamine concentration can decrease in response to chronic, intense

interval training (17), and as a result of overtraining (18, 25, 31, 33). Plasma

concentrations of less than 0.5 mM have been observed in resting athletes during intense

training (17, 18). Furthermore, increased incidence of infection was observed in athletes


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with decreased plasma glutamine concentration (18), although this outcome is not

consistently reported (25). Controversial evidence exists for the efficacy of glutamine

supplementation on immune indices and infection incidence in athletes engaged in intense

exercise. In two literature reviews of glutamine supplementation, exercise, and immune

indices, it was concluded that changes in plasma glutamine concentration most likely do

not play a role in changes in immune indices, including salivary IgA concentration, and

that glutamine supplementation would not beneficial to athletes (16, 30). However, it

should be noted that all research to date has only involved acute supplementation during

and after a single bout of exercise.

The effect of chronic, high-dose glutamine supplementation on the immune system

of human athletes during overload training has not been investigated. Unlike acute

exercise, which may only marginally affect glutamine homeostasis for a short period of

time, repetitive and intense training may repeatedly challenge glutamine homeostasis and

adversely affect certain immune cell functions (29). Intense exercise may induce small

transient decrements in plasma glutamine concentration, which are manifested by a greater

decline in glutamine availability to mucosal tissues (29). Repetitive reductions in

glutamine supply to IgA-producing lymphoid cells could affect their ability to produce IgA

and increase susceptibility to infection. Under such conditions, chronic glutamine

supplementation would, theoretically, help maintain glutamine homeostasis and sIgA

concentration. No studies, to date, have attempted to utilize chronic glutamine

supplementation to prevent the decrease in secretory IgA associated with intense training.

In addition, only the effects of intense exercise on salivary IgA have been reported in the

literature. However, some pathogens, such as rhinovirus, only infect nasal mucosa (14).


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Thus, investigation of the effects of supplementation and intense training on nasal IgA is

warranted.

The purpose of this study was to determine whether chronic, high-dose glutamine

supplementation would affect salivary and nasal IgA during a nine-day, intense interval

training program. We hypothesized that supplementation would attenuate training-induced

decreases in plasma glutamine and sIgA concentrations.

METHODS

Subject recruitment and cohorts

Thirteen healthy runners (four females and nine males) were recruited by

advertisement within the local community. Inclusion criteria required subjects to: 1) be

between the ages of 18 and 49 years; 2) currently run a minimum of 20 miles per week, and

3) have a peak whole body oxygen uptake (VO2 peak) of at least 52.5 ml.kg

-1min

-1for males

or 41.0 ml.kg-1min-1 for females. These values are classified as superior according to

Coopers aerobic fitness classifications (5). Exclusion criteria included: self-reported

respiratory illness within seven days prior to training, prescription/non-prescription drug

use, smoking, obesity, use of dietary supplements other than a multivitamin, illegal drug

use, food/caffeine intake less than eight hours prior to testing, alcohol intake less than eight

hours prior to testing, injury which impedes training, illness, diabetes, pregnancy, any

heart, respiratory, or liver condition that contraindicated intense exercise training, and any

other health condition that contraindicated intense exercise training. Washington State

Universitys Institutional Review Board approved the study and written consent was

obtained before data collection. Subjects were compensated $100 upon successful

completion of the study. The subjects were randomly assigned to receive glutamine (G, n =


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6) or placebo (P, n = 7). A male subject from the placebo group withdrew after the second

testing day due to self-diagnosed URTI. Because this subject completed two testing days,

his data were included in the final analysis.

Testing and Training

During the week prior to the commencement of the study, subjects were given an

orientation to the testing and training procedures. Testing was conducted at the Exercise

Science Human Physiology Laboratories at Washington State University. Subjects were

tested for body mass, body composition, and peak oxygen uptake during treadmill running.

The treadmill protocol was performed according to a modification of a protocol described

by Fry et al. (10). Briefly, subjects walked or ran on the treadmill at a self-selected speed

and grade as a warm-up for a self-selected period. Subjects then ran for four min at 12

km.h

-1and a 1% incline. After a three min rest, subjects ran for four min at 15 km

.h

-1and a

1% incline. After another three min rest, subjects ran to volitional exhaustion at 18 km.h-1

and a 1% incline. Whole body oxygen uptake was measured using an open circuitry, on-

line gas analysis system (Sensormedics, Loma Linda, CA). Body mass was determined by

a standard laboratory scale. Bioelectrical impedance (Omron, Vernon Hills, IL) was used

to assess subject body composition. Heart rate was monitored every 30 s telemetrically

(Polar, Woodbury, NY).

Training took place on outdoor or indoor tracks according to a modification of

protocol of Fry et al. (10). Subjects participated in 9-9 days of twice a day interval

training, beginning on day 1, the day of initial testing. Subjects performed a warm-up at a

self-selected pace for a self-selected time. Morning sessions were conducted between 6 - 9

AM and included 15 x 1 min runs performed separated by two min recovery, where


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subjects were permitted to walk briskly. Afternoon sessions were conducted between 4-8

PM and involved 10 x 1 min run periods separated by one min recovery. Subjects ran at a

pace approximate to the speed of the final stage that they reached during the preliminary

treadmill test. If subjects were not able to maintain the required pace, the distance was

reduced by 25 m until the subject was able to maintain pace. Heart rates were monitored

telemetrically via Polar Vantage XL heart rate monitors. All training sessions were

supervised. A 96% compliance rate was obtained. Reasons for absences from training

included: participation in races on the day of training and complaints of muscle pain from

training. The training period was followed by a 5-day recovery period where subjects

returned to their normal daily exercise or physical activities.

Subject Testing

Testing was performed on day 1 (T1), days 6-7 (T2), day 11 (T3), and day 16 or

day 18 (T4). Subjects arrived at the lab between 6-8 AM after an overnight fast. Subjects

were requested to not brush their teeth before they came to the lab, and to have not

consumed food or beverage (with the exception of water), or exercise for at least eight

hours prior. Subjects provided blood, nasal wash, and stimulated saliva samples, and each

subject filled out a Profile of Mood States (POMS) questionnaire (26). Total mood

disturbance, a composite mood assessment, was determined according to Morgan et al.

(27). At T4, two of the subjects failed to comply with the no-exercise requirement prior to

testing. Samples were collected from these subjects approximately three hours post-

exercise. The values for these subjects were not greater than one standard deviation from

the mean of the group, and therefore, their data were included in the analysis.

Blood


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The blood samples (~ 15 mL) were obtained via venipuncture of an antecubital

vein. The blood was collected into heparinized vaccutainers. Hematocrit was measured by

microcentrifugation. Hemoglobin concentration was determined using the

cyanmethemoglobin technique. Plasma volume changes were estimated according to Dill

and Costill (7).

Diet

Three-day dietary food records were obtained for days 1-3 or 3-5 and for days 12-

14. Diets were analyzed for average daily caloric, protein, carbohydrate, and fat content

using Diet Analysis Plus (ESHA Research, Salem, OR).

Supplementation

Subjects received 0.1 g.kg-1 of L-glutamine (Experimental and Applied Sciences,

Golden, CO) mixed with sugar-free Lemonade (Safeway, Inc., Pleasanton, CA) or a

placebo (sugar-free lemonade only) four times daily for 14 days beginning on the first day

of training. Subjects were blinded to which treatment they received. The

supplement/placebo was mixed in approximately 300 mL of water. Supplement and

placebo were identical in appearance and taste when mixed. Subjects consumed the drinks

immediately after preparation. Subjects were instructed to consume no protein for 30 min

to avoid competition of other amino acids. During the training period, the first dose was

provided immediately after the morning session. The next dose was provided midway

between the morning and afternoon session. The third dose was provided immediately

after the afternoon session. The last dose was provided in the evening. During the

recovery period, subjects were given their supplement packets ahead of time with


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instructions on how to prepare the drink. They were also given a sheet on which to record

the times when they consumed the supplement. A 99.7% compliance rate was achieved.

Plasma Glutamine and Total Protein Determination

Plasma samples deproteinized with ice cold 10% perchloric acid and neutralized

with KOH were analyzed for glutamine by enzymatic determination according to the

manufacturers instructions (Sigma Aldrich, St.Louis, MO). The detection range for this

assay is 0.14 - 1.4 mM L-glutamine. Salivary and nasal total protein was analyzed

spectrophotometrically according to Bradford (1). The technicians performing all the

biological assays were blinded to the treatments that the subjects received.

Saliva Collection

Saliva flow was stimulated by chewing a single parafilm (5 cm2) section for a one

min, which typically elicits 1-3 mL..min

-1of flow (6). Subjects were encouraged to allow

the saliva to accumulate in the mouth until the urge to swallow occurred. Without

expectorating, the subjects allowed the saliva to flow into the collection tube and repeated

the entire process until time elapsed. The sample was immediately placed on ice and then

centrifuged to remove cellular debris. The supernatant fluid was frozen at -80 C for later

analysis of IgA and protein concentration.

Nasal Wash

Nasal washes were collected as follows. The subjects head was tilted back at an

angle of approximately 70 from vertical. While the subject closed his/her glottis, a rubber

bulb syringe containing approximately seven mL of sterile phosphate-buffered saline (PBS)

was inserted into a nostril. The subject then tilted his/her head forward to allow the wash

to drip into a sterile cup. The wash sample was immediately placed on ice and then


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centrifuged to remove cellular debris. The supernatant fluid was frozen at -80 C for later

analysis of IgA and protein concentration.

IgA

Nasal wash and saliva samples were analyzed for IgA concentrations using an

enzyme linked immunosorbent assay. Briefly, 96-well polystyrene plates were coated with

goat antihuman IgA (alpha chain specific, Sigma) diluted in 0.05M carbonate buffer and

incubated overnight at 4C. The residual fluid was gently removed and 1% bovine serum

albumin in PBS added to the wells as a blocking agent. The plate was incubated for one

hour at 37C. After gently removing the fluid, human IgA standards (Sigma), saliva and

nasal samples (diluted 1:500) were added to the wells. The plate was incubated for one

hour at 37C and then washed with PBS/Tween. After gently removing residual fluid,

peroxidase conjugate anti-human IgA (Sigma) was added to each well and the plate

incubated for one hour at 37C. The plate was washed and the fluid gently removed. The

substrate, O-Phenylenediamine in 0.05M phosphate-citrate buffer and 0.03% H202, was

added prior to a 30-min incubation at 37C. The reaction was stopped with 2.5 M HCL

and absorbance read at 490nm (Molecular Devices Corporation, Sunnyvale, CA).

Statistics

Subject demographic data between groups, cohorts, and gender were compared

using an independent t-test. In cases of unequal variances, an Aspin-Welch unequal

variance t-test was used. All other data were modeled using a linear mixed model

estimated by a restricted maximum likelihood (REML) algorithm. Treatment was included

as the between-subject factor, time was included as the repeated within-subjects factor, and

time by treatment was included as the interaction. For heart rate data, training session was


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also included as repeated within-subjects factor, with all possible interactions among time,

treatment, and session included in the model. Repeated covariance structures were

specified as unstructured, compound symmetry, first-order autoregressive, or toeplitz,

depending on which structure resulted in the best model fit as determined by Hurvich and

Tsais Criterion (AICC). For salivary, nasal, glutamine, and POMS data, baseline values

were included in the model as a covariate. If the covariate was not significant, it was

removed from the model. Due to low sample size and statistical power, gender was not

included as a factor in any mixed model analyses. The normality-of-residuals assumption

required by the REML algorithm was checked using a one-sample Kolmogorov-Smirnov

test on the residuals and via visual inspection of a histogram of the residuals. All data

satisfied the normality-of-residuals assumption.

If significant interactions were present,post-hoc analyses on simple main effects

within each factor level were done using multiple t-tests with a Sidak adjustment. If no

significant interactions existed,post-hoc analyses on main effects were done using multiple

t-tests with a Sidak adjustment. Main effects for salivary IgA, salivary IgA:protein,

salivary IgA output, nasal IgA:protein, and plasma glutamine, were declared significant at a

one-tailed critical alpha of .05. All interactions, and all other main effects, were tested

using the null hypothesis and were declared significant at a two-tailed alpha of .05.

Spearman-rank correlations were determined between plasma glutamine and IgA measures,

plasma glutamine and POMS variables, POMS variables and IgA measures, nasal

IgA/protein and salivary IgA output, and plasma glutamine and dietary protein intake.

Separate correlations were performed for variables where a significant effect of treatment

existed for the placebo group and glutamine group. Otherwise, correlations were


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conducted using data from all subjects. All analyses were performed using NCSS 2000

(Kaysville, UT) and SPSS 12.0 (Chicago, IL). All data are reported as means standard

error of the mean (SEM).

RESULTS

Physical and physiological characteristics

Subject physical and physiological characteristics were as follows: Males: n = 9,

body mass 73.52.9 kg, VO2 peak 57.82.3 ml/kg/min, age 29.33.8 yr; Females: n = 4,

body mass 61.63.8 kg, VO2 peak 50.32.6 ml/kg/min, age 28.54.4 yr. There were no

significant treatment or group differences in body mass, height, VO2 peak, age, body fat

percentage, lean body mass, or fat mass. Height, body mass, and lean body mass were

significantly higher in males than females (P < .05). There were no significant gender

differences for any other variable. There was no significant effect of treatment on changes

in plasma volume (P = .08). There was a significant effect of time (P = .001). The percent

change in plasma volume from baseline at T4 (3.6% 1.6) was significantly less than at T2

(13.6% 2.9; P = .048) and T3 (18.4% 4.3; P = .001).

Training Heart Rate

There was no significant difference between G and P groups in HR, expressed as a

percentage of age-predicted MHR, at each training session (89.7% 0.4 and 89.3% 0.5 for

P and G groups, respectively, P = .80). HR in the afternoon/evening sessions was higher

than the heart rates in the morning sessions (90.3% 0.4 and 88.7% 0.4, respectively; P =

0.0), and HR steadily decreased from 92.8% 0.6 on the first full day of training to 87.6%

1.2 on the last day of training.

Plasma Glutamine Concentration and Diet


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There was no significant effect of treatment (P = .14) on plasma glutamine

concentration (Figure 1). There was a significant effect of time (P = .043; Figure 1). Post-

hoc analysis did not reveal any significant differences among days. The training and

glutamine supplementation protocols did not significantly change caloric intake (P = .21

and P = .62, respectively; Table 1), protein intake (P = .60 and P = .16, respectively; Table

1), carbohydrate intake (P = .32 and P = .95, respectively; Table 1), or fat intake (P = .47

and P = .51, respectively; Table 1).

Salivary and Nasal IgA

The treatment and training protocols did not significantly alter salivary flow rate (P

= .67 and P = .47, respectively; Figure 2), salivary IgA concentration (P = .41 and P = .10,

respectively; Figure 3A), salivary IgA output (P = .17 and P = .48, respectively; Figure

3C), and salivary protein concentration (P = .53 and P = .23, respectively; Figure 4). There

was a significant time by treatment interaction for salivary IgA relative to total salivary

protein (P = .021; Figure 3B). Post-hoc analysis revealed that in the placebo group,

salivary IgA/protein was signicantly greater at T2 compared to T1 (P = 0.022; Figure 3B)

and T3 (P = .044; Figure 3B). Salivary IgA/protein was also significantly greater at T2 in

P as compared to G (P = .011; Figure 3B). There was no significant effect of time on nasal

IgA relative to protein (P = .48, Figure 5). There was a significant treatment effect on nasal

IgA per protein content, with the overall mean lower in the P group (264.7 35.0 g/mg

vs. 172.4 33.7 g/mg, P=.047; Figure 5).

POMS

Measures of vigor, fatigue, and composite mood were significantly changed during

the training protocol (Table 2). Post-hoc analysis revealed that vigor was significantly


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reduced at T3 compared to T1 (P = .024). Fatigue was significantly increased at T2

compared to T1 (P = .013) and T4 (P = .014). Total mood disturbance was significantly

increased at T2 (P = .003) and T3 (P = .01) compared to T4. Measures of anger,

depression, confusion, and tension were not significantly altered by treatment or time

(Table 2).

Correlational Analyses

Statistically weak associations were observed between IgA measures and POMS

indices indicating that POMS scores could not be used as markers of changes in secretory

IgA with training. A significant correlation was observed for salivary flow rate and vigor

(P = .01, r = 0.34)

DISCUSSION

Plasma glutamine concentration decreased significantly with training, which is

consistent with Keast et al. (17) who reported a significant decrease in plasma glutamine

concentration in five military recruits during a 9 day, twice-per-day interval training

protocol. The mechanisms behind the reduction in plasma glutamine concentration in

response to overload training are not currently known but may include renal uptake of

glutamine to maintain acid-base balance under conditions of exercise-induced acidosis

(34).

Plasma glutamine concentration was highly variable with a range of 0.18 0.80

mM and independent of glutamine supplementation. The variability did not reflect

differences in training intensity, because some subjects with low plasma glutamine

concentrations had the lowest % MHR during exercise. It is also unlikely that diet directly

influenced glutamine concentration because protein intake did not change over the course


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of the study. The diets were however, self-reported and precise determination of protein

intake was not possible.

Glutamine supplementation four times per day would be expected to increase the

average daily concentration of plasma glutamine. An oral dosage of 0.1 g.kg

-1increases

plasma glutamine concentration by 50% within 30 min after administration and glutamine

concentration returns to baseline within 90-120 min (40). The lack of a significant effect of

supplementation in this study can be attributed to the time span of least eight hours between

the last daily glutamine dose and the early morning blood draw in fasted subjects.

Nasal IgA concentration relative to total protein was significantly increased by

chronic glutamine supplementation during training. Covariate analyses indicated that this

effect was independent of baseline group differences. It is not clear why chronic glutamine

supplementation would selectively increase nasal IgA concentration but have no effect on

salivary IgA content. Differences may be due to collection of unstimulated nasal fluid

samples versus stimulated salivary samples. Stimulation by chewing increases epithelial

cell transcytosis of IgA into salivary fluid (32) and may have masked the effects of chronic

glutamine supplementation on basal IgA secretion in non stimulated samples.

To our knowledge, we are the first to report an effect of glutamine supplementation

on nasal IgA during training. It is possible, due to the low power of the test that this effect

occurred by random chance. However, this result seems unlikely given that 83% of the

subjects receiving chronic glutamine supplementation demonstrated an increase in nasal

IgA per protein between T1 and T3 whereas, 63% of the placebo group had a decrease in

this variable during the same period. Increasing the sample size would increase the power


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of the test. Due to the large variability in nasal IgA concentration, a sample size of at least

32 subjects per group would be required to attain a statistical power of at least 0.80.

Investigation of nasal IgA in athletic populations at increased risk for URTI is

warranted because some viruses that cause URTI, such as rhinovirus, only infect nasal

mucosa (14). The relationship between nasal IgA and infection risk is not as well studied.

Intranasal treatment with nasal IgA reduced the risk of respiratory syncytial virus in rhesus

monkeys (39). Lindberg and Berglund (20) observed that intranasal treatment with IgA did

not reduce risk of URTI symptoms in world-class canoeists over a 17-day period. There

are no studies to date, which include direct evaluation of the relationship between

endogenous nasal IgA and URTI risk.

Supplementation had no effect on salivary IgA concentration or salivary IgA

output. These findings are consistent with Krzywkowski et al. (19), who reported that

glutamine supplementation provided during and after an acute bout of cycle ergometer

exercise failed to prevent the post-exercise decrease in salivary IgA. The results of the

present investigation conflict with other studies in which decreases in salivary IgA

concentration have been observed (2, 13, 21, 35). The disparity may relate to the duration

of the training period used in protocols. The present study included a training period of

approximately nine days, which may not have provided a sufficient stimulus to reduce

early morning salivary IgA in resting subjects. Others have observed decreases in salivary

IgA concentration following longer training periods. Gleeson et al. (13) observed that pre-

exercise salivary IgA concentration in elite swimmers decreased by 4.1% per month during

seven months of training. Tharp and Barnes (35) reported that salivary IgA concentration

in elite swimmers were significantly lower during one month of heavy training versus one


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month of light or moderate training. Others have reported decreases in sIgA (2) and

salivary IgA/protein ratio (21) after approximately three weeks of strenuous training.

Salivary IgA:protein ratio increased at T2 in the placebo group and was greater at

this time than values observed for the supplemented group. This can be attributed to the

non-significant increase in salivary IgA at T2 in P (P = .054; Figure 3A), with a

concomitant lack of change in salivary protein (Figure 4). The increase in salivary IgA

concentration at T2 in P is most likely due to a reduced salivary flow rate, which also

occurred at this time (Figure 2).

Overload and overtraining are associated with mood disturbances (9, 10, 15, 27)

and reduced secretory IgA concentrations and secretion rates (4, 11, 28). In the present

study, vigor decreased and fatigue increased with interval training and returned to baseline

after the recovery period. These observations are in agreement with the findings of others

(15, 27, 37). Overall, correlational analyses failed to identify POMS scores as indicators of

changes in sIgA during training.

In conclusion, chronic, high-dose glutamine supplementation during nine days of

interval training had no effect on salivary IgA concentration or output or plasma glutamine

concentration in resting athletes. However, supplementation resulted in higher nasal IgA

during training. The biological significance of this effect on nasal IgA (i.e., whether it

helps reduce an athletes risk of URTI during intense periods of training) remains to be

demonstrated.


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ACKNOWLEDGEMENTS

We thank our subjects for participating in this study and Dr. Kathe Gabel, Dr. Phil

Mixter, Dr. Jackie Banasik, Sara Minier, Jennifer Wilberding, and Jessica Moore for their

technical assistance. This study was financed by a grant from Experimental and Applied

Sciences (EAS), Golden, Colorado, and Washington State University Spokane.

Current address for primary author:

James Krieger

Department of Food Science and Human Nutrition

University of Florida

P.O. Box 110370

359 FSHN Building

Newell Drive

Gainesville, FL 32611-0370


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Figure 1: Plasma glutamine concentration in glutamine (G) and placebo (P) groups over

time. Training and supplement duration are shown as solid and dashed lines,

respectively. Data represent means SEM, n = 6 per group, with the exception of T1 and

T2, where n = 7 in the P group. There was a significant effect of time (P < .05).


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Figure 2: Salivary flow rate in chronic glutamine supplemented and placebo groups.


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Figure 3: Salivary IgA concentration (A), concentration relative to protein (B), and output

(C) in chronic glutamine supplemented and placebo groups. * Significantly different from G

at T2 (P < .05). Significantly different from T1 and T3 (P < .05)


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Figure 4: Salivary protein concentration in chronic glutamine supplemented and placebo

groups.


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Figure 5: Nasal IgA relative to protein in chronic glutamine supplemented and placebo

groups. There was a significant effect of treatment (P < 0.05).


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TABLE 1.Dietary intake

Glutamine Placebo P-value P-value

for treatment for time

Kilocalories (Record 1) 2262 174 2569 348

Kilocalories (Record 2) 2627 264 2688 327 0.62 0.21

Protein (g, Record 1) 80.2 8.6 111 11.4

Protein (g, Record 2) 97.0 14.2 104 8.1 0.16 0.60

Carbohydrates (g, Record 1) 297 19 314 38

Carbohydrates (g, Record 2) 345 33 322 51 0.95 0.32

Fat (g, Record 1) 88.2 11.2 101 17.9

Fat (g, Record 2) 93.5 11.0 106 15.2 0.51 0.47

Values are means SEM. Record 1 represents the food record for days 1-3 or 3-5.

Record 2 represents the food record for days 12-14.


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TABLE 2. POMS variables at each time point

T1 T2 T3 T4

Confusion 4.9 1.0 6.4 1.5 6.0 1.1 4.2 1.3

Tension 6.0 1.0 6.4 1.1 5.3 0.9 5.2 1.0

Depression 3.9 1.2 3.7 1.2 2.3 1.0 1.5 0.9

Anger 4.4 0.8 3.3 0.9 3.5 1.2 2.2 0.7

Vigor* 19.7 1.0a

16.8 1.4a,b

15.8 1.7b

18.4 1.9a,b

Fatigue* 6.1 0.6a

11.8 1.4b

10.8 1.5a,b

4.5 0.9a,c

Composite* 105.6 3.5a,b 114.8 5.2a 112.1 4.7a 99.1 5.0b

Group data are combined in this table. Values are means SEM. n = 13 for T1 and T2,

and n = 12 for T3 and T4. * Significant main effect of time (P < 0.05). Within each

variable, different letters are significantly different from each other as determined by

Sidakpost-hoc analysis.

chronic glutamine supplementation increases nasal but not salivary iga during nine days of interval...

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