Medicine & Science in Sports & Exercise:
Clinical Sciences: Clinically Relevant
Effects of progressive resistance training on immune response in aging and chronic inflammation
RALL, LAURA C.; ROUBENOFF, RONENN; CANNON, JOSEPH G.; ABAD, LESLIE W.; DINARELLO, CHARLES A.; MEYDANI, SIMIN NIKBIN
Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111; School of Human Development and Nutritional Sciences, University of Wisconsin, Stevens Point, WI 54481; Tupper Research Institute, Department of Medicine, New England Medical Center and Tufts University School of Medicine, Boston, MA 02111; and Noll Laboratory, Pennsylvania State University, State College, PA 16802
Submitted for publication June 1995.
Accepted for publication January 1996.
The authors thank Dr. Gerard Dallal for statistical assistance; the staff of the Nutrition Evaluation Laboratory and the nursing staff of the Metabolic Research Unit at the Human Nutrition Research Center for their devoted assistance; Arlene Tenney for assistance with recruitment; and lastly, our volunteers for their dedication to this work.
This study was supported by NIH Grant DK02120 (RR), an Arthritis Foundation Clinical Science Grant (RR), and USDA Contract 53-K06-01 from the U.S. Department of Agriculture, Agricultural Research Service.
The contents of this publication do not necessarily reflect the views or policies of the U. S. Department of Agriculture, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.
Address for correspondence: Simin Nikbin Meydani, JMUSDAHNRCA at Tufts University, 711 Washington Street, Boston, MA 02111.
The effects of 12 wk of progressive resistance strength training onin vivo and in vitro immune parameters were evaluated in a controlled study of eight subjects with rheumatoid arthritis (RA), eight healthy young (22-30 yr), and eight healthy elderly (65-80 yr) individuals. Six healthy elderly (65-80 yr) nontraining control subjects were also evaluated to account for seasonal and psychosocial effects. Training subjects exercised at 80% of their one-repetition maximum and performed eight repetitions per set, three sets per session on a twice weekly basis. Peripheral blood mononuclear cell (PBMC) subpopulations, cytokine and prostaglandin (PG) E2 production, proliferative response, and delayed type hypersensitivity (DTH) skin response were measured before and after 12 wk of training. Training did not induce changes in PBMC subsets, interleukin(IL)-1 β, tumor necrosis factor-α (TNF), IL-6, IL-2, or PGE2 production, lymphocyte proliferation, or DTH response in any of the training groups compared with control subjects. These data suggest that 12 wk of high-intensity progressive resistance strength training does not affect immune function in young or elderly healthy individuals or subjects with RA.
Although an acute bout of exhaustive exercise leads to dramatic changes in immune response, the effects of progressive resistance training on the immune system remain unclear (reviewed inrefs. 6,23,24,43). Most studies have examined various immune parameters in response to a single, acute exercise challenge in which transient changes in circulating levels of leukocyte and lymphocyte subsets (18,33), decreases in proliferative response (19,28,44), and increases in circulating interleukin-1 (IL-1) bioactivity(7) have been described. Cannon et al.(7) first demonstrated that endogenous pyrogen, now known as IL-1, which mediates the acute phase response to infection, is also released during acute exercise. Since that time additional work(8,9) has supported the notion that damaging exercise initiates an acute phase response that may contribute to metabolic alterations after exercise. Although some studies(26,32,34) have addressed the effects of aerobic training on various immune parameters, virtually none have examined whether strength training leads to similar effects via the immune system as an acute, severe bout of exercise. Further complicating the situation are the many physiological (age or menstrual cycles if studying young women), psychological (life stresses), and environmental (circadian and seasonal) factors that can themselves affect the immune system, leading to potentially spurious results if appropriate controls are not included.
Few studies have included subjects of different age groups to examine the age-related differences in immune response after exercise training. Several of the same immune parameters that are transiently affected by acute exercise are also those that are altered during aging. An age-associated decline in T-cell mediated immune parameters is well recognized and is characterized by a reduced lymphocyte proliferative response, decreased frequency and size of delayed type hypersensitivity responses, decreased IL-2 production by T cells, and alterations in T-cell subsets (reviewed in refs. 29,30). The effects of exercise training on these already diminished immune parameters is unknown. Recently, there has been increasing emphasis on the benefits of strength-training exercises among elderly individuals in terms of improved muscle strength and function (16,38), increased muscle mass (17), and weight control(5). Undoubtedly, there are many positive effects of strength training for the elderly. However, given the complex series of changes in many physiological systems that occur as a result of exercise training, the ultimate impact on the immune system is difficult to predict. Therefore, given the age-related declines in immunity, understanding the impact of strength training (which is being increasingly recommended to these individuals) in terms of the immune response is critically important.
Even less is known about the effect of exercise in patients with autoimmune disorders in whom the immune system is inappropriately activated. Like the elderly, individuals with the chronic inflammatory condition rheumatoid arthritis (RA) demonstrate reduced physical performance capacity, and it has been increasingly recognized that exercise of varying types leads to improvements in physical performance capacity, cardiorespiratory fitness, muscle strength, and activities of daily living without exacerbating clinical disease progression or joint damage(14,21,35,36,38). However, subjects with RA also exhibit an altered resting cytokine profile with increased IL-1 and TNF production by PBMC (40). The effects of an exercise training regimen on the activated immune system of these subjects, compared with healthy individuals, remain to be elucidated. The present study was designed to investigate the effects of a 12-wk progressive resistance training program controlled for seasonal and psychosocial factors on in vivo and in vitro T-cell mediated immune parameters in young and elderly healthy men and women compared with patients with RA.
Subjects and Experimental Design
Subjects and study design have been described in detail elsewhere(37). Briefly, eight subjects with RA (25-65 yr), eight healthy young (22-30 yr) and 14 healthy elderly (65-80 yr) sedentary men and women were studied. Before acceptance in the study, all subjects passed a complete physical exam, completed a maximal O2 uptake(˙VO2max) test on a cycle ergometer, and provided written informed consent. All healthy young and RA subjects underwent 12 wk of strength training, while the healthy elderly subjects were randomly assigned to either a strength training (elderly exercise, N = 8) or nonstrength training control group (elderly control, N = 6). Elderly subjects were chosen for the nonstrength training control group because these subjects are most likely to be influenced by the social and psychological aspects of the study (increased social interaction and individualized attention), which may affect the immune system. All of the subjects with RA met the American College of Rheumatology criteria for RA (1) and were considered by their rheumatologist to be under good disease control with a stable medication regimen for at least 3 months prior to entering the study. All study groups had the same proportion of females and males as the RA group(≈66%), which approximated the ratio of females to males affected by RA in the U.S. population (46). The project covered a 2-yr period, and subjects from each group initiated training at random times throughout the year to avoid clustering of one group during any particular season. Potential subjects had no known medical illnesses other than RA and were not consuming vitamin or mineral supplements or any medications (other than subjects with RA) that might affect the immune system, such as oral contraceptives, corticosteroids, antibiotics, aspirin, or nonsteroidal anti-inflammatory drugs (NSAID). Prednisone and methotrexate use among subjects with RA is detailed in Table 1. The research protocol was approved by the New England Medical Center/Tufts University Human Investigation Review Committee.
All subjects were admitted to the metabolic research unit (MRU) of the Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University(HNRCA), Boston, MA for baseline studies. Thereafter, all subjects visited the HNRCA twice a week for 12 wk of either strength training (young exercise, elderly exercise, and subjects with RA) or swimming only (elderly control subjects). Subjects were admitted to the HNRCA a second time for follow-up studies at the end of the 12 wk.
Prior to their baseline admission, subjects' usual diet was determined as previously described (37). Intake and body weight were monitored on a weekly basis throughout the study, and subjects were counseled as needed to achieve stable weight and maintain their usual dietary intake. Diets were analyzed by computer using Food Processor II software (ESHA Research, Salem, OR).
At baseline and follow-up, heparinized blood (67 ml) was collected from subjects on two consecutive days (24 and 48 h after the last exercise session at follow-up) for in vitro immunological tests, 3 ml was collected without additives for a serum preparation, and 3 ml of blood was collected in EDTA for white blood cell count differential analysis. Two blood samples at each phase were collected to control for day-to-day variability in these tests: mean values of the two days were used for statistical analysis. Blood was drawn in the fasting state between 7:30 and 8:30 a.m. for all subjects throughout the study. For young female subjects blood was drawn during the late luteal or early follicular phase of the menstrual cycle. Two subjects with RA required a change in their medication regimen mid-study: one subject discontinued NSAID use, and the other began taking 5 mg·d-1 of prednisone after discontinuing gold due to an allergic reaction. Data from these subjects were excluded from analysis where noted. Delayed type hypersensitivity skin tests were administered on day 1 of each admission, and the diameter of induration was measured 24 and 48 h after application.
Subjects randomized to exercise training underwent a 12-wk regimen of progressive resistance strength training of all major muscle groups on a twice weekly basis. All subjects maintained their habitual physical activities but performed no additional strength training. Sessions were separated by 2-3 d of rest. Subjects trained at 80% of their one-repetition maximum (maximal weight that can be lifted once with acceptable form), on five different machines for the trunk (abdominal and back extension), upper body (chest press), and lower body (leg press and leg extension) strength. Acceptable form means that the exercise is performed by the specific muscle group involved without the help of the whole body or other muscle groups. All subjects exercised on Keiser pneumatic resistance equipment (Keiser Sports Health Equipment, Fresno, CA). Strength testing was performed at baseline and every 2 wk thereafter, and the exercise load was increased accordingly to maintain a constant training intensity. Subjects performed three sets of eight repetitions on each machine with 2-min rest periods between sets, and training sessions lasted approximately 45 min. Each session was preceded by a warm-up period consisting of approximately 15 min of water exercises (calisthenics and 10 min of water walking). Subjects in the elderly control group performed this in-water component only. All sessions were supervised by either LCR or RR.
Isolation of Mononuclear Cells
Peripheral blood mononuclear cells (PBMC) were separated from heparinized whole blood according to the procedure of Boyum (4). Peripheral blood mononuclear cells were removed from the interface and washed twice in endotoxin-free RPMI-1640 culture media (RPMI) (Bio-Whittaker, Walkersville, MD) supplemented with 100 μg·ml-1 penicillin, 100 mg·ml-1 streptomycin, 2 mmol of l-glutamine·l-1 and 25 mmol HEPES·l-1 (Gibco, Grand Island, NY). Cells were suspended in RPMI and counted under a light microscope. Cell viability was determined using the trypan blue exclusion method. Cells were then suspended at appropriate concentrations for further immunologic assays. Cells were cultured both with and without indomethacin(1.25 × 10-4 mg·ml-1 in absolute ethanol) (Sigma Chemical Co., St. Louis, MO) to account for NSAID use among subjects with RA. A sample of heparinized plasma was heat inactivated at 56°C for 30 min to be used as autologous plasma (5%) in the lymphocyte proliferation, IL-2, IL-6, and PGE2 cultures, and a sample of heat-inactivated serum (1%) was used for IL-1 and TNF production in cultures.
Lymphocyte proliferation was measured by 3H-thymidine incorporation following stimulation with T-cell mitogens. Dilutions of mitogens between 1μg·ml-1 and 100 μg·ml-1 for phytohemagglutinin (PHA) (Difco Laboratories, Detroit, MI) and 10μg·ml-1 and 100 μg·ml-1 for concanavalin A(Con A) (Sigma Chemical Co.) were prepared in RPMI and 100 μl was plated in triplicate into 96 well, flat-bottomed microtiter plates (Becton Dickinson, Oxnard, CA). Peripheral blood mononuclear cells were suspended at 2 × 106 cells·ml-1 in RPMI with 20% autologous plasma. Fifty microliters of the cell suspension and 50 μl of indomethacin or media control were plated with and without mitogens and incubated for 72 h at 37°C in an atmosphere of 5% CO2 and 95% humidity. Four hours before termination of incubation 18.5 μBq of 3H-thymidine (specific activity 247.9 GBq·mol-1, New England Nuclear, Boston, MA) in 20μl was added to each well. Cells were harvested onto glass microtiter filter paper by a cell harvester (PHD, Cambridge, MA). Filter disks were placed in minivials and counted in a liquid-scintillation counter (Beckman Instruments, Palo Alto, CA). The counter has an efficiency of 50% for3 H. The results are reported as corrected counts per minute (ccpm), the average counts per minute of mitogen-stimulated cultures minus the average counts per minute of cultures without mitogens.
Fluorescence Activated Cell Sorting
Cells were suspended at a concentration of 107 cell·ml-1 in cold phosphate buffer solution (PBS) with 0.1% sodium azide and 2% fetal calf serum. Fifty microliters of suspended cells were incubated with 10 μl of each of the following monoclonal antibodies: anti-Leu-3a FITC (CD4+), anti-Leu-2a FITC (CD8+), anti-Leu-4 PE(CD3+), and 5 μl of anti-Leu-12 PE (CD 19+) (Becton Dickinson) for 30-45 min on ice. Mouse IgG1 and IgG2 antibodies were used as controls. After incubation, 3 ml of cold PBS (containing 0.1% sodium azide and 2% fetal calf serum) weres added to the cells and gently vortexed. Cells were centrifuged at 300 × g for 10 min at 2-8°C. To fix the cells, 0.5% paraformaldehyde was used. Flow cytometric analysis was done by FACS®CAN (Becton Dickinson, San Jose, CA) as described (22). Gates were set at 2. The ratio of forward scatter to side scatter was 6.
Cytokine and Eicosanoid Measurements
IL-1 and TNF. Cells were cultured in 96-well flat-bottomed microtiter plates at a final well concentration of 2.5 × 106 cells·ml-1. Each well contained 50 μl cells in RPMI plus 100μl of either RPMI alone, 10 ng·ml-1 endotoxin(lipopolysaccharide from Escherichia coli Serotype 0111:B4, Sigma Chemical Co.) in RPMI, or 20 organisms/cell of heat-killed Staph epidermidis in RPMI also. All wells contained 20 μl of 10% heat-inactivated autologous serum (final well concentration of 1%); 50 μl of either indomethacin or RPMI was also added to each well. After 24 h at 37°C in an atmosphere of 5% CO2 and 95% humidity, cell-free supernatants were stored at -70°C for later analysis of secreted IL-1 and TNF. Plate wells were refilled with 200 μl RPMI and frozen at -70°C prior to three freeze-thaw cycles to lyse the cells for later analysis of cell-associated IL-1 and TNF.
Measurement of both secreted and cell-associated IL-1 and TNF production were carried out in duplicate by specific, noncross-reacting radioimmunoassays(RIA) as described previously (15,45). Cytokine determinations below the detection limit of the assay were assigned the value at the detection limit. The interassay variability of samples was < 10%, and the intra-assay variability was ≤ 5% for both cytokines. Samples from baseline and follow-up were measured in the same assay.
IL-2, IL-6, and PGE2. Five × 105 cells·ml-1 (final well concentration) in RPMI with 20% autologous plasma were cultured in 24-well flat-bottomed plates (Becton Dickinson) with PHA (100 μg·ml-1) and Con A (100μg·ml-1) for 48 h in an atmosphere of 5% CO2 and 95% humidity. Cell-free supernatants were stored at -70°C for later analysis. IL-2 activity was measured using a microassay method described by Gillis et al. (20). Recombinant human IL-2 (Genzyme Corp., Cambridge, MA) was used as the standard. One unit·ml-1 is defined as the amount of recombinant IL-2 that causes a half maximal incorporation of 3H-thymidine in 5 × 103 CTLL-2 in culture(cytotoxic T-cell line, ATCC #214-TIB, Rockville, MD). IL-2 activity was calculated using probit analysis (20). IL-6 was measured by radioimmunoassay (RIA) as previously described (41). Prostaglandin E2 was measured by commercial enzyme immunoassay (Cayman Chemical Co., Ann Arbor, MI), which is 100% specific for measuring PGE2 and PGE3. Human subjects consuming the typical American diet such as those in this study do not produce detectable levels of PGE3. The intra- and interassay coefficients of variation for this assay are ≤ 10%. All samples were measured in the same assay.
Complete Blood Cell Count and White Cell Differntial
Complete blood cell count was obtained using a Baker 9000 Hematology Analyzer (Serono-Baker Instrument Inc., Allentown, PA) and white cell differential was assessed by microscopic examination of blood smears following Wright-Giemsa staining.
Delayed Type Hypersensitivity Skin Test
Delayed type hypersensitivity, an in vivo measure of T-cell mediated immune function, was assessed using a battery of seven antigens[tetanus toxoid, diphtheria toxoid, streptococcus (group C), old tuberculin(mycobacterium tuberculosis and mycobacterium bovis), candida (albicans), trichophyton (mentagrophytes), and proteus (mirabilis)] available as Multi-Test CMI (Connaught Laboratories, Inc., Swiftwater, PA), which applies the antigens simultaneously and uniformly through separate applicator heads. The diameter of induration was measured 24 and 48 h after administration of the test on the forearm, and the maximum response was used for scoring. The number of positive responses was calculated as the total number of positive antigens and the cumulative index was calculated as the total diameter of induration of all the positive reactions. According to the manufacturer's instructions, an induration of ≥ 2 mm was considered positive. The test was administered to each subject by the same physician before and after exercise whenever possible, and the diameter of induration was measured by the same person in all cases. Repeated administration of this test has been shown not to be associated with a boosting effect (27).
All reported values are mean ± SD. Nonnormally distributed data were transformed prior to analysis. Unless otherwise noted, since there were no differences in results from assays done with and without indomethacin, results without indomethacin added to cell cultures are reported. Comparisons between groups at baseline and follow-up were done by analysis of variance (ANOVA) with Tukey's HSD test. For each outcome of interest, the difference between follow-up and baseline values was calculated for each of the four study groups. The magnitude of the difference for each of the three intervention groups (RA, young, elderly exercise) was compared with the difference found in the elderly control group by ANOVA. Statistical significance was taken atα = 0.05 and β = 0.80. Sample size was calculated usingPC-SIZE: Consultant (12). All data analysis was performed using SYSTAT Version 5.2 (SYSTAT, Inc., Evanston, IL).
Subject characteristics at baseline are shown in Table 1. There were no differences between groups of subjects in terms of body weight or body mass index (BMI); these parameters did not change between baseline and follow-up. Young subjects had a significantly lower sedimentation rate (speed at which erythrocytes settle when anticoagulant is added to blood) compared with all other groups of subjects at both baseline and follow-up; there was no change in this parameter owing to exercise. For subjects with RA, disease duration and number of patients taking prednisone, methotrexate, and NSAID are shown in Table 1. Blood cell parameters(erythrocyte, hemoglobin, hematocrit, platelet count) were within normal ranges in all subject groups and did not change during the study (data not shown). White blood cell and differential counts were also within normal ranges and did not change significantly during the study period in any subject group (data not shown). Subjects with RA had significantly lower percentages of lymphocytes and greater percentages of neutrophils compared with all other subject groups at both baseline and follow-up (P < 0.05), but, after adjusting for prednisone use, this difference was no longer evident. There were no differences between groups at baseline or within groups between baseline and follow-up in dietary intake of nutrients such as vitamin E,β-carotene, or vitamin B6, which might affect immune response (reviewed in ref. 31) (data not shown).
The results of the strength training program have been described in detail elsewhere (37). Briefly, all three training groups of subjects demonstrated similar improvements in mean strength (calculated as the average one-repetition maximum on five machines) after 12 wk of progressive resistance exercise compared with the ≈9% change seen among nonstrength training control subjects: RA 57% (P < 0.0005), young exercise 44% (P < 0.01), and elderly exercise 36% (P < 0.05).
Tumor necrosis factor-α production by PBMC is shown inTable 2 under unstimulated, LPS-stimulated, and S. epidermidis-stimulated conditions. At baseline, there were differences between subject groups in the amount of cytokine produced: production of secreted TNF at baseline in response to S. epidermidis was 50% greater among elderly exercisers and subjects with RA compared with young subjects (P < 0.05). Baseline cell-associated TNF in response to LPS was also lower in young subjects than the other groups (P < 0.005 vs RA; P < 0.05 vs elderly control; and P = 0.06 vs elderly exercise). There were no differences in unstimulated TNF production between groups at baseline although the same pattern of lower production in young subjects compared with elderly subjects and subjects with RA was observed. There were no significant changes as a result of the training intervention in either secreted or cell-associated TNF production among any of the training groups compared with control subjects. While training led to an increase in cell-associated TNF under unstimulated conditions in the RA group, there was a decrease related to training among elderly subjects (P< 0.05, RA vs elderly exercise) and no change among the young subjects.
As with TNF, there were no changes in secreted or cell-associated IL-1 production between baseline and follow-up (Table 3). Furthermore, the only differences between groups were among the elderly control subjects, who had lower secreted (P < 0.05 vs elderly and young exercise at baseline), and cell-associated (P < 0.01 vs elderly exercise at baseline) unstimulated IL-1 production.
Subjects with RA did have higher cell-associated IL-1 Ra production at baseline compared with young subjects (S. epidermidis-stimulated,P < 0.05), and there was a significant increase as a result of training among the young subjects compared with controls (S. epidermidis-stimulated, P = 0.05).
There were no significant differences in IL-6 (unstimulated or Con A-stimulated) or IL-2 (Con A- or PHA-stimulated) production after 12 wk of strength training and no differences between groups at baseline(Table 4). Phytohemagglutinin-stimulated IL-2 production, but not Con A-stimulated, was significantly increased in cultures with indomethacin compared with those without indomethacin; however, there were no differences between or within groups in either case (data not shown).
Table 5 shows the percentages of CD3+, CD4+, CD8+ T cells, and the CD4+/CD8+ ratio, and CD19+ B cells. There were no changes in any of these parameters after strength training. However, at baseline the CD4+/CD8+ ratio was higher in the elderly exercise than young exercise subjects (P < 0.05) and subjects with RA (P = 0.07). This was largely as a result of a lower percentage of CD8+ cells in elderly exercise subjects.
Lymphocyte proliferation in response to optimal concentrations of PHA (10μg·ml-1) and Con A (50 μg·ml-1) is shown inTable 6. There was no change in lymphocyte proliferation as a result of strength training and no differences between groups at baseline.
Prostaglandin E[inb]2 Production
There were no differences among groups at baseline in terms of PGE2 production and no changes as a result of strength training(Table 6).
Delayed Type Hypersensitivity
Neither the cumulative diameter of induration nor the total number of positive responses changed after strength training in any of the subjects(Table 7). There were also no differences among groups at baseline.
The results of this study indicate that 12 wk of progressive resistance exercise in young and elderly healthy subjects and patients with RA does not lead to large changes in in vivo (DTH) or in vitro(cytokine and PGE2 production, lymphocyte proliferation, and subsets) immune parameters when measured at least 24 h after a training session. These effects of training are unlike an acute bout of exercise in which transient shifts in many of these immune parameters(7,19,25,28) and muscle damage mediated by products of the immune system (8,9) have been described. Furthermore, the response to exercise training of both elderly individuals and patients with an autoimmune disorder, RA, is not different from that of young healthy subjects.
To our knowledge, no previous studies have examined the effects of strength training on immune response in a controlled fashion to account for normal temporal changes (circadian and seasonal) and psychosocial effects associated with exercise training. In this study, circadian effects were controlled by drawing blood at the same time of day on all subjects. Seasonal effects were controlled as the project covered a 2-yr period and subjects from each group initiated training at random times throughout the year. Psychosocial effects were accounted for by including nonstrength training control subjects who received similar attention and social interaction as the training subjects. Only elderly subjects were included as nonexercising controls due to financial limitations of the study and the belief that elderly individuals would be most susceptible to nonphysical effects of exercise.
To determine the effect of training per se on immune response, we compared the change within each training group between baseline and follow-up with the change among the control subjects. Subjects in the control group had changes between baseline and follow-up ranging from approximately 5 to 25%, depending on the parameter. Such changes are unrelated to strength training, but rather, are secondary to other factors such as seasonal or psychosocial effects or individual variability. Among subjects who underwent strength training, the changes between baseline and follow-up ranged from less than 1% to approximately 40%, depending on the parameter and subject group.
Sample size for this investigation was originally calculated based on expected changes in strength (37), protein metabolism(39), and changes in cytokines of 50-100% that might be considered biologically meaningful as this is the magnitude of increase observed in various disease states such as RA(13,40), sepsis (10), and multiple sclerosis (42). Table 8 shows a sensitivity analysis table, including each of the immune variables presented here, to illustrate the observed maximum change for each outcome variable compared with the number of subjects needed to detect a change of 25%, 50%, 100%, and 200%, based on the variability that we observed. There were no significant differences between subject groups in their responses to training. For several of the immune parameters, the standard deviation of the difference between baseline and follow-up was greater than the mean difference, suggesting a large amount of variability in terms of the individual subjects' response to training. Eight subjects per group would have been adequate to detect changes of 50-100% for each of the immune parameters measured, with the exception of PGE2 (Table 8). Furthermore, it is noteworthy that studies of acute bouts of exercise in which significant changes in circulating levels of leukocyte and lymphocyte subsets(18,33), decreases in proliferative response(19,28,44), and increases in IL-1(7) have been described had sample sizes comparable to ours. Therefore, sample size does not appear to be a limiting factor in drawing conclusions regarding biologically meaningful changes in the present study. In most cases, the changes within training groups were either similar to or less than those among our nonstrength training control subjects, suggesting that any training effect at all is relatively small in the presence of the other factors that may influence immune response.
Our results regarding the lack of an effect of strength training on immune parameters in subjects with RA agree with the recent findings relating to aerobic training of Baslund et al. (3). Eight weeks of progressive bicycle training in eight elderly (>65 yr) patients with RA had no effect on PBMC subpopulations, proliferative response, natural killer cell activity or plasma IL-1 α, IL-1 β, or IL-6 compared with control subjects with RA. This study differs from ours in that plasma levels (as opposed to PBMC production) were measured. Furthermore, these investigators chose moderate interval training to avoid possible induction or enhancement of monokines by intense exercise, which could increase inflammation. However, our findings demonstrate that high-intensity strength training in subjects with RA, performed at a level equal to young and elderly healthy subjects, does not exacerbate a preexisting inflammatory condition, and furthermore, improves strength and functional capacity in those individuals whose arthritis is well-controlled by medication at the start of the study(37).
An earlier study of moderate exercise training and immune response has been reported in 36 premenopausal women who underwent 15 wk of a walking program (5 d·wk-1, 45 min per session, at 60% of heart rate reserve)(32). This type of exercise was associated with a mild decrease in the percentage of lymphocytes and number of T cells but demonstrated no change in the helper/suppressor T-cell ratio or lymphocyte function as measured by spontaneous blastogenesis. Despite the differences between the type of exercise regimen and subjects in this and the present study, the findings of no change in lymphocyte function or the helper/suppressor ratio are similar to our results, and both contrast with those changes reported immediately following an acute bout of exercise.
Yet another way in which exercise training and immunity have been studied is using subjects whose habitual activity includes regular, rigorous training. Baj et al. (2) measured the total number of leukocytes, T-lymphocyte subsets, lymphocyte proliferation, and IL-2 production in 15 young cyclists at the beginning and end of an intensive 6-month training and racing season compared with healthy young sedentary male control subjects. Training consisted of cycling approximately 500 km·wk-1; this regimen led to significant increases in ˙VO2max, maximal workload, and duration of cycle-ergometer exercise tests performed before and after training. Significantly decreased CD3+ and CD4+ cells, decreased IL-2 production, and increased lymphocyte proliferation were observed after the training season in the cyclists but not in the control subjects. However, these results are not directly comparable to our study given the differences in subjects and type of training. Furthermore, subjects were not excluded from the study for vitamin or mineral use, and no information is provided as to their diet or which subjects were actually consuming supplements. Given the reported effects of even moderate vitamin supplement use at levels comparable to the recommended dietary allowances on immune parameters(11), it cannot be concluded with certainty that the results from this study are attributable to the training alone. Lastly, differences in psychological stress between cyclists and control subjects could also be present and could affect the T-cell parameters that were measured (6).
In summary, our data support the concept that 12 wk of progressive resistance exercise in young and elderly healthy individuals and patients with RA does not lead to the biologically important alterations in immune response that are seen after an acute bout of exercise. Not only are there benefits in terms of strength and body composition changes as a result of exercise training, but there are also no major negative effects on the immune parameters measured in this study, regardless of age or the presence of autoimmune disease. In drawing conclusions about the effects of exercise on immunity, it is important to be highly specific as to the type, intensity, and duration of exercise, the time post-exercise that measurements are taken, the parameters being studied, and the subjects involved. Failure to do so can lead to conflicting results and confusion in the literature regarding the impact of exercise on immunity.
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