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Protein metabolism in rheumatoid arthritis and aging. Effects of muscle strength training and tumor necrosis factor ╨Ю┬▒

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ARTHRITIS & RHEUMATISM
Vol. 39, No. 7, July 1996, pp. 1115-1124
0 1996, American College of Rheumatology
1115
PROTEIN METABOLISM IN RHEUMATOID ARTHRITIS AND AGING
Effects of Muscle Strength Training and Tumor Necrosis Factor a
LAURA C. RALL, CLIFFORD J. ROSEN, GREGORY DOLNIKOWSKI, WILBURTA J. HARTMAN,
NANCY LUNDGREN, LESLIE W. ABAD, CHARLES A. DINARELLO, and RONENN ROUBENOFF
Objective. To determine the effects of rheumatoid
arthritis (RA) on whole-body protein metabolism.
Methods. We examined protein metabolism and
its hormonal and cytokine mediators before and 12
weeks after progressive resistance muscle strength
training in 8 healthy young (mean k SD age 25 2 2
years) and 8 healthy elderly (70 rt 5 years) men and
women, and in 8 adults with RA (42 2 13 years). An
additional 6 healthy elderly subjects (69 k 3 years)
served as a swimming-only control group.
Results. Subjects with RA had higher rates of
protein breakdown than did young or elderly healthy
subjects (79.9 f 17.2 versus 60.3 f 5.8 and 63.7 2 12.4
pmoles/gm total body potassium/hour, respectively, P <
0.05), while there was no effect of age per se. Patients
treated with methotrexate had normal rates of protein
breakdown ( P < 0.01 versus RA without methotrexate;
P not significant versus healthy young subjects). Increased protein catabolism in RA was no longer evident
The contents of this publication do not necessarily reflect the
views or policies of the US Department of Agriculture, nor does
mention of trade names. commercial products, or organizations imply
endorsement by the US government.
Supported by NIH grants DK-02120 and AI-15614, an Arthritis Foundation Clinical Science grant, USDA contract 53-K06-01, and
Boston Obesity Nutrition Research Center grant POlDK46200.
Laura C. Rall, PhD, RD. Gregory Dolnikowski, PhD, Wilburta J. Hartman, PhD, Nancy Lundgren: Jean Mayer USDA Human
Nutrition Research Center on Aging at Tufts University, Boston,
Massachusetts; Clifford J. Rosen, MD: Maine Center for Osteoporosis
Research and Education, St. Joseph Hospital, Bangor; Leslie W.
Abad, Ronenn Roubenoff, MD, MHS: Jean Mayer USDA Human
Nutrition Research Center, and Tupper Research Institute, Tufts
University School of Medicine and New England Medical Center,
Boston, Massachusetts; Charles A. Dinarello, MD: Tupper Research
Institute, Tufts University School of Medicine and New England
Medical Center, Boston, Massachusetts.
Address reprint requests to Ronenn Roubenoff, MD, MHS,
JMUSDA-HNRCA at Tufts University. 711 Washington Street, Boston, MA 02111.
Submitted for publication December 12, 1995; accepted in
revised form February 16, 1996.
after strength training. In multiple regression analysis,
levels of tumor necrosis factor a (TNFa) (r = 0.47, P =
0.01) and growth hormone (r = -0.51, P = 0.006) were
associated with protein breakdown, and plasma glucagon levels were inversely correlated with protein synthesis (r = -0.45, P =0.02). Growth hormone (r = -0.56,
P = 0.002) and glucagon (r = 0.45, P = 0.04, levels were
associated with protein oxidation.
Conclusion. Adults with RA have increased
whole-body protein breakdown, which correlates with
growth hormone, glucagon, and TNFa production.
Despite the many advances in our understanding
of the disordered immune response that occurs in rheumatoid arthritis (RA), little information has been available about the effect of inflammation on metabolism and
body composition in RA. Previous work from our laboratory has shown that body cell mass and physical
activity are significantly reduced, and resting energy
expenditure (REE) significantly increased, in patients
with RA compared with healthy age-, sex-, race-, and
weight-matched controls (1-3). This hypermetabolism of
RA (defined as an increase in REE by > l o % above
predicted levels) was directly associated with the production of tumor necrosis factor a (TNFa) and interleuk i n - l p (IL-1p) by peripheral blood mononuclear cells
(PBMC) from these patients, which was approximately
2-fold higher than that in the control subjects. We have
termed the cytokine-associated loss of lean body mass in
RA rheumatoid cachexia, and have proposed that this
cachexia is an important contributor to morbidity and
mortality in RA, and offers insights into inflammatory
mediators of cachexia (4).
Understanding the mediators of the decline in
body cell and protein mass is important because loss of
more than -40% of baseline body cell mass is fatal, as
shown in starvation, aging, and in acute illness (5). In
1116
addition to the influence of the classic neuroendocrine
hormones on protein metabolism, there is considerable
evidence that IL-1p and TNFa can mediate protein
metabolism during acute illness (for review, see ref. 6 ) .
During the initiation of the acute-phase response to
injury or infection, for which the production of IL-1p
and TNFa is fundamental, several systemic changes
contribute to the observed metabolic alterations (7).
Along with increases in insulin, glucagon, and hepatic
protein synthesis and a relative decline in growth hormone (GH) and insulin-like growth factor 1 (IGF-l),
there is a pronounced catabolism of muscle protein,
accompanied by loss of body cell mass, negative nitrogen
balance, and development of cachexia (8). Similar, but
less pronounced, changes in body composition and the
pattern of whole body protein synthesis and breakdown
also occur during aging (for review, see ref. 6). Depending on whether protein turnover is expressed per kilogram
of body weight or per kilogram of lean body mass, whole
body protein turnover in elderly individuals has been
reported to either decline (9) or remain unchanged (10).
Because catabolism (defined as a negative protein balance) must occur in order for cachexia to develop, we sought to measure protein turnover in two
situations characterized by a slow loss of lean body mass:
RA and healthy aging. Inasmuch as the changes in body
composition and energy expenditure in RA mirror those
in aging but occur independently of chronologic age, it is
possible that RA could provide insight into immune
mechanisms related to the loss of cell mass with aging.
Because protein metabolism accounts for a large part of
REE, we hypothesized that the conditions of patients
with RA would be catabolic as well as hypermetabolic.
Although most clinicians are familiar with nitrogen balance studies for determining protein balance,
these are not precise enough for such metabolic research. Over the past 2 decades, stable-isotope infusions
which track the fate of a tracer dose of a labeled amino
acid have become the accepted method for determining
protein flux (turnover), oxidation, and synthesis (11). In
the present study, "C-leucine was infused as a tracer to
determine whole-body protein kinetics. Leucine has
certain advantages over other amino acid tracers, because as a branched-chain amino acid, it is metabolized
directly in the muscle without the need for hepatic
metabolism. The labeled carbon from infused leucine
appears in the circulation as '3C-ketoisocaproic acid
(KIC) after intracellular deamination of leucine, and has
been shown to be in equilibrium with leucyl-transfer
RNA (tRNA): which represents the pool of interest
(leucine available for incorporation into new protein)
RALL ET AL
(11). Thus, measurement of the appearance of KIC in
the circulation allows the calculation of leucine flux or
turnover, from which whole-body protein flux can be
calculated. Leucine in the body can either be used for
protein synthesis (in which case the 13Cdisappears from
the circulation and is incorporated into protein), or it
can be oxidized for energy (in which case the label
appears in the breath as 13C0,). The present study is the
first to apply this technique to RA.
We also sought to examine the effects of the only
physiologic stimulus known to improve catabolism,
which is progressive resistance exercise (PRE), and to
test the hypothesis that PRE would improve (or at least
not worsen) protein catabolism in RA. We have recently
shown that intensive PRE leads to large improvements
in muscle strength and functional status in selected
patients with RA, without worsening joint symptoms
(12). We report here that protein breakdown is increased in RA, and we delineate for the first time the
relationship between protein metabolism, hormone status, and cytokine status before and after muscle strength
training in subjects with RA and in healthy young and
elderly controls.
PATIENTS AND METHODS
Study subjects. Eight untrained subjects with RA (ages
25-65) and 8 untrained healthy young (ages 22-30) and 14
untrained healthy elderly (ages 65-80) men and women were
studied. All healthy young and R A subjects underwent 12
weeks of muscle strength training, while the healthy elderly
subjects were randomly assigned to either a strength training
(elderly exercise group; n = 8) or non-strength training control
group (elderly control group; n = 6). Only elderly subjects
were randomized to a non-strength training control group
because these subjects are most likely to be affected by the
possible nonphysical effects of exercise (because of increased
social interaction and individualized attention).
All of the patients with RA met the American College
of Rheumatology (formerly, the American Rheumatism Association) criteria for RA (13), and their disease was considered
by their rheumatologist to be under good control. Patients with
RA had to have a stable medication regimen for 6 months
prior to entering the study; thus, all had low disease activity,
but represented a range of disease severity.
All study groups had the same proportions of females
and males (-66% female), which approximated the ratio of
females to males who are affected by RA in the US population
(14). Potential subjects were excluded if they were obese (body
mass index >30 kg/m2) or had diabetes, cancer, renal disease,
liver disease, coronary artery disease, endocrine disorders, or
any autoimmune disease other than RA. The research protocol
was approved by the New England Medical Centernufts
University Human Investigation Review Committee.
Study design. All subjects were admitted to the metabolic research unit (MRU) at the Jean Mayer USDA Human
PROTEIN METABOLISM IN RA AND AGING
Nutrition Research Center on Aging at Tufts University
(HNRCA), Boston, MA, for 3 days of baseline studies. Thereafter, all subjects visited the HNRCA on a twice-weekly basis
for 12 weeks of either strength training (young exercise, elderly
exercise, and RA) or swimming only (elderly control). Subjects
were admitted to the HNRCA an additional time for 3 days of
followup studies at the end of the 12 weeks.
Diet. The subjects' usual diet was determined in telephone interviews conducted by a registered dietitian (LCR)
during the month prior to their baseline admission, by 24-hour
diet recall on 7-10 nonconsecutive days. The composition of
each subject's usual diet was used to design an isocaloric,
isonitrogenous, meat-free diet to be followed for 3 days, before
and during their baseline stay in the MRU, thereby preventing
any acute dietary changes that could interfere with metabolic
studies. Diet (by 24-hour recall) and body weight were monitored on a weekly basis during the 12-week study period, and
subjects were counseled as needed to achieve weight maintenance and a protein intake between 1.3 and 1.5 gm/kg/day.
Diet recalls taken during the last month of the study were used
to determine the subjects' usual diet at followup and to design
a diet for their followup admission that was similar to that at
their baseline admission. The Food Processor I1 (ESHA
Research, Salem, OR) was used for computer analysis of all
diet recall data.
Exercise intervention. All subjects warmed up by performing a series of stretching exercises in a warm (84°F) pool,
and by swimming or water-walking for 10 minutes. Subjects
assigned to exercise training then exercised all major muscle
groups, on a twice-weekly basis, separated by 2 to 3 days of
rest. Subjects assigned to the control group performed only the
warm-up regimen. All subjects maintained their habitual physical activities, but performed no additional strength training.
Resistance was set at 80% of the 1-repetition maximum (maximal weight that can be lifted once with acceptable
form). Strength testing was performed at baseline and every 2
weeks, and as strength progressed, the exercise load was
increased accordingly to maintain a constant training intensity
of 80%. All subjects exercised on Keiser pneumatic resistance
equipment (Keiser, Fresno, CA), using machines for the torso,
upper body, and lower body. Subjects performed 3 sets of 8
repetitions on each machine, and training sessions lasted
45-60 minutes.
CH and IGF-1 measurements. At approximately 6:30
AM on day 2 of the subjects' admission to the MRU. a catheter
was inserted into an antecubital vein for blood sampling at
20-minute intervals for 24 hours, beginning -30 minutes after
venipuncture. Subjects ate 3 meals per day (8:30 AM, 12:OO PM,
and 5:30 PM) and were encouraged to move about. Plasma
samples for IGF-1 measurements were obtained at 8:00 AM in
the fasting state, and all samples were frozen at -70°C for later
assay.
Serum GH concentrations were determined in duplicate in each sample by a technician who was blinded to the
subject's identity and training status, by immunochemiluminometric assay (Nichols Laboratories, San Juan Capistrano, CA).
Intra- and interassay coefficients of variation (CV) ranged
from 4% to 9% (15). The assay sensitivity was 0.02 ng/ml.
Values given below are the mean of the 72 time points.
Samples for testing IGF-1 were prepared for measurement by acid-ethanol cryoprecipitation to separate IGF-1
1117
from IGF binding proteins (IGFBPs). This technique reduces
residual IGFBPs to a level that does not interfere with the
IGF-1 assay (16). Samples were measured in duplicate with a
single radioimmunoassay kit (Nichols Laboratories). The intraassay CV was 3.75%. Measurements of IGFBP-3 were made
m duplicate with a single immunoradiometric assay kit (Diagnostic Systems, Webster, TX). The intraassay CV for IGFBP-3
was 5.05%. The molar ratios of IGF-I and IGFBP-3 were
calculated using molecular weights of 7.5 kd for IGF-1 and 30
kd for IGFBP-3.
Leucine infusion. On day 3 of each residence period
(at least 72 hours after the final exercise session at followup),
a primed continuous infusion of L-[ 1-"C]-leucine was administered for 4 hours to determine leucine flux, oxidation, and
synthesis. In this method, labeled leucine is infused until a
steady-state has been reached, and the appearance of KIC in
the blood has been shown to be in equilibrium with intracellular leucyl-tRNA, thus allowing a valid estimate of whole-body
protein flux (11). Leucine is especially suited for this task
because it is a branched-chain amino acid, and thus, is principally metabolized in muscle and not in the liver.
Sampling of expired breath for the presence of 13C0,
allows the determination of leucine (and thus whole-body
protein) oxidation, in which the labeled carbon from the
infused leucine is exhaled as labeled CO,. All subjects were
studied in the postabsorptive state. At -7:30 AM, after an
overnight fast, a second catheter was inserted in retrograde
manner into a hand vein for blood sampling. Venous blood
samples were arterialized by keeping this hand at 38°C
throughout the infusion procedure. The catheter previously
inserted for the 24-hour blood draw was utilized for isotope
infusion. At -8:30 AM, the isotope infusion was begun, with the
administration of priming doses of NaH13C0, (0.2 mg/kg;
Cambridge Isotope Laboratories, Andover, MA) and L-[ 1"C]-leucine (7.6 pmoles/kg; Cambridge Isotope Laboratories). The L-[l-'3C]-leucine was diluted in sterile saline and
infused using a calibrated syringe pump (Harvard Apparatus,
Natick, MA) for 4 hours, at a rate of 0.318 ml/minute (0.127
pmoles/kg/minute).
Blood samples were obtained 60 minutes prior to the
infusion and hourly for the first 2 hours, then every 30 minutes
during the third hour and every 20 minutes for the last hour.
Plasma (or serum for KIC) was separated immediately by
centrifugation at 4°C and kept frozen at -70°C for subsequent
analysis of isotopic enrichments. Samples for measurement of
insulin, glucose, cortisol, and glucagon were collected at 60,
150, and 240 minutes during the infusion, in the fasting state.
Plasma samples for glucagon assay were collected into tubes
containing EDTA-Trasylol, and samples for insulin and glucose assay were cpllected into tubes containing potassium
oxalate/sodium fluoride. These samples were frozen immediately after separation.
Plasma glucagon (Diagnostic Products, Los Angeles,
CA) and insulin (ICN Biomedicals, Costa Mesa, CA) were
measured by radjOimmunoassay by the HNRCA Nutrition
Evaluation Laboratory. Plasma glucose was measured by enzyme kinetic reaction (Roche Diagnostics, Nutley, NJ). Serum
cortisol was measured by a commercial assay (Nichols). The
assay sensitivity was 0.8 pg/dl.
Samples of expired air were collected for measurement
of l3C0, enrichment, using an anesthesia bag and were
RALL ET AL
1118
Table 1. Characteristics of the study subjects at baseline*
F U patients
Young exercise controls
(n = 8)
Age, years
Sex, no. femalelno. male
Weight, kg
BMI, kg/mz
Total body potassium, gm
Duration of RA, years
Prednisone, no. taking (mg/day)
Methotrexate, no. taking (mg/week)
41.8 i 12.6
513
65.9 IT 15.9
25.0 t 4.3
88.3 i 18.2
14.6 ? 12.5
5 (7.0 -C 3.7)
4 (13.8 i 3.2)
(n
=
Elderly exercise
controls
(n
8)
25.8 t 2.5
513
65.5 i- 4.5
3-23 t 2.4
117.9 2 26.9t
-
=
8)
Elderly controls
(n = 6)
70.3 t 5.0
513
70.6 i- 15.5
25.1 IT 2.8
99.9 t 29.7
68.8 2 2.9
412
63.7 ? 11.3
23.2 Z 3.4
85.6 t 13.6
-
-
-
-
-
-
* Except where noted otheiwise, values are the mean t SD. See Patients and Methods for descriptions of groups. RA
=
rheumatoid arthritis; BMI
body mass index.
t P < 0.05 versus elderly control group.
=
transferred to a 15-ml evacuated collection tube (Venoject;
Terumo, Elkton, MD). Carbon dioxide production rates were
determined prior to the start of the infusion, and at 150 and
225 minutes during the infusion, using a ventilated hood
system as previously described (3). 13C enrichment of plasma
KIC was determined as its quinoxalinol-t-butyldimethylsilyl
ether derivative by gas chromatography-mass spectrometry
(model 5888P; Hewlett-Packard, Palo Alto, CA) (17). 13C
enrichment of expired CO, was measured by isotope r a t i e
mass spectrometry (SIRA-10; Fisons Instruments, Danvers,
MA) (18). Measurement of L-[l-'3C]-leucine in the infusates was
performed using a Beckman 6300 analyzer (Beckman Instruments, Palo Alto, CA) with Turbochrom 111 2700 chromatography software (Perkin Elmer Nelson Systems, Cupertino, CA) for
peak integration.
Other measurements. Total body potassium was measured in a whole-body counter, as described previously (3).
Cytokine production by PBMC was measured by specific,
non-cross-reacting radioimmunoassay as described previously
(19,20). The interassay variation of samples was <lo% and the
intraassay variation was 5 5 % . Samples from baseline and
followup were measured in the same assay. Values shown for
IL-1p and TNFa production represent total (secreted plus
cell-associated) cytokine production in response to Staphylococcus epidemidis stimulation. Levels of IL-6 shown are in
response to concanavalin A (100 pg/ml) stimulation.
Calculation of leucine kinetics. Leucine metabolism
was calculated using the stochastic model of Matthews et a1
(21). Under this model,
Flux = oxidation
+ synthesis = intake + breakdown
In the fasting state, intake = 0; therefore, the rate of leucine
release from protein breakdown equals the calculated flux.
Leucine flux was calculated from the plasma enrichment of
KIC to reflect the intracellular leucine pool (22) and to
eliminate sampling site inconsistencies (23). Leucine oxidation
was calculated from "CO, production and isotopic enrichment
of KIC in plasma, corrected using a bicarbonate retention
factor of 0.70 (24). The rate at which leucine was incorporated
into protein synthesis was calculated as flux minus oxidation.
Statistical analysis. Values are reported as the mean
? SD. The distribution of each variable was examined graphically and statistically, and non-normally-distributed data were
log-transformed prior to analysis. Comparisons between
groups at baseline and followup were tested by analysis of
variance (ANOVA) with Tukey's honestly significant difference test. To assess the effect of training alone on any observed
change, differences within strength-trained groups (followup
minus baseline) were compared with differences within the
control group by ANOVA. Data presented for plasma insulin,
glucose, cortisol, and glucagon are from samples taken at the
60-minute time point during the leucine infusion. Pearson's
correlation coefficient was used to express the relationship
between measures of interest, and Bonferroni adjustments
were performed to correct significance levels for multiple tests.
Multiple linear regression techniques were used to analyze the
effects of independent variables on the outcome variables of
leucine flux, oxidation, synthesis, urinary 3-methylhistidine
excretion, serum GH, and plasma glucagon. The regression
coefficient ( p ) and standard error of p are presented. Statistical
significance was taken at a = 0.05. All data analysis was
performed using SYSTAT version 5.2 (SYSTAT, Evanston, IL).
RESULTS
Subject characteristics, diet, and training effects.
The effects of the exercise intervention on strength, diet,
functional status, and body composition have been published recently (12). The subjects' characteristics at
baseline are presented in Table 1.
Patients with RA had well-controlled disease,
with a mean (+SD) of 3.4 -C 2.3 painful joints and 2.9 -t
4.5 swollen joints on physical examination. They reported a mean (+SD) pain scale score of 5.5 -+ 3.5
(15-cm visual analog scale) and had a mean (+SD)
disability score of 1.0 -t 0.8 on the Health Assessment
Questionnaire, indicating mild to moderate disability
(25). Their erythrocyte sedimentation rate (ESR) was
mildly elevated (mean -C SD 36.6 -t 14.9 mm/hour). Five
of the 8 patients were taking prednisone (mean + SD
dosage 7.0 -t 3.7 mg/day), and 4 were taking methotrexate (mean ? SD dosage 13.8 -t 3.2 mdweek). However,
PROTEIN METABOLISM IN FL4 AND AGING
1119
T
80
...............
T
'O0/I
............... . . . .
...
L
3
0
jmf
...
60
I-
€
P
u)
a, 40
0
5
20
RA
Young
A
Elderly
Control
0
Pred ( + )
Pred (-1
B
MTX ( + 1 MTX (-)
Figure 1. A, Leucine flux (whole bars), oxidation (open areas), and synthesis (hatched areas) at baseline (left-hand bars) and followup (right-hand
bars), by study group: patients with rheumatoid arthritis (RA) and healthy young and elderly muscle strength-trained subjects and healthy elderly
control (swimming only) subjects. * = P = 0.01 versus young group, and P = 0.05 versus elderly exercise group. B, Leucine flux, oxidation, and
synthesis in EL4 patients before exercise training, by prednisone and methotrexate (MTX) treatment status. ** = P < 0.01 versus patients not taking
MTX. Values are the mean and SEM. TBK = total body potassium.
the disease severity (accumulated damage) was greater
than the current disease activity: the mean duration of
RA was 14.6 2 12.5 years, and the mean (-tSD)
functional class was 2.2 -+ 0.8 (maximum possible 4.0).
Four patients had had 7 joint replacements: both hips in
1 patient, 1 hip and several phalangeal joints in 1 patient,
and 1 hip in 2 patients. Thus, the goal of recruiting
patients with well-controlled RA of moderate-to-severe
disease (functional deficit) was met.
There were no between-group differences in body
weight or body mass index. Total body potassium, which
measures body cell mass, was greater in young than in
elderly control subjects at baseline ( P < 0.05). There
were no within-group changes in any of these parameters between baseline and followup. After 12 weeks
of progressive resistance exercise, all 3 groups of
strength training subjects improved their muscle
strength (calculated as the average 1-repetition maximum on 5 machines) to a similar extent compared with
non-strength training control subjects: RA group 57%
( P < 0.0005), young exercise group 44% ( P < O.Ol), and
elderly exercise group 36% ( P < 0.05). These results
have been presented in greater detail elsewhere (12).
There were no between-group differences in either energy or protein intake at baseline, nor were there
any significant differences in intake between the baseline
and followup admissions. Mean (-+SD)energy intake for
all subjects combined was 28.0 t 3.0 kcalkgJday at
baseline, and 31.2 2 3.8 kcalkg/day at followup. Mean
(+SD) protein intake was 1.1 2 0.08 gm/kg/day at
baseline, and 1.3 -+ 0.19 gm/kg/day at followup.
Leucine kinetics. The rates of leucine flux, oxidation, and synthesis expressed per gm of total body
potassium (i.e., normalized for between-subject differences in body cell mass) are presented in Figure 1.
Leucine flux, a reflection of whole-body protein turnover, was measured in the postabsorptive state, and as
expected, breakdown was greater than synthesis among
all groups at both baseline and followup ( P < 0.001).
Subjects with RA had higher leucine flux at baseline
compared with both elderly exercise (P = 0.05) and
young (P = 0.01) groups (Figure 1A). There were no
differences in leucine flux between groups at followup,
nor were there any differences between groups in terms
of leucine oxidation or synthesis at either baseline or
followup, since the group X time interaction term was
RALL ET AL
1120
Table 2. Hormone and cytokine levels in the study subjects*
RA patients
(n = 8)
GH (ng/ml)
Baseline
Followup
IGF-I (ng/ml)
Baseline
Followup
IGFBP-3 (ng/ml)
Baseline
Followup
IGF- l/IGFBP-3
Baseline
Followup
Insulin (pIU/ml)
Baseline
Followup
Glucagon (pg/ml)
Baseline
Followup
Cortisol (pg/dl)
Baseline
Followup
TNFa (nglml)
Baseline
Followup
IL-lp (ndml)
Baseline
Followup
1L-6 (ng/ml)
Baseline
Followup
0.77 2 0.46
0.91 i- 0.70
Young exercise
controls
(n = 8)
Elderly exercise
controls
(n = 8)
Elderly controls
(n = 6)
2.18 2 0.74t
1.94 ? 0.86$
0.84 2 0.65
0.67 2 0.45
0.45 i- 0.46
0.62 i- 0.82
79.7 ? 24.13
85.4 2 30.28
130.5 ? 46.3
141.3 i- 61.1
162.1 ? 39.8
166.2 i- 39.8
144.5 i- 45.8
142.9 i- 33.3
2.837 2 694
2,899 i- 837
3,360 ? 404#
3,285 i- 402
3,148 ? 590
3,104 2 581
2,548 t 203
2,648 ? 234
0.18 ? 0.05
0.19 i- 0.06
0.20 i- 0.05
0.20 ? 0.05#
0.18 2 0.06
0.19 i- 0.04
0.13 i- 0.05
0.13 t 0.05
7.5 -t 3.2
8.6 i- 3.7
10.6 f 5.2
9.9 i- 4.4
10.2 ? 3.3
10.9 2 4.2
9.0 i- 4.5
7.3 ? 2.6
88.8 2 28.0
84.9 t 32.6
113.5 i- 23.8
101.5 -t 29.0
107.8 t 19.8
111.4 t 47.1
87.5 2 46.8
69.5 2 42.7
7.9 2 4.3
6.4 i- 3.9
9.9 ? 2.5
12.7 ? 4.8**
9.4 -t 3.1
7.7 f 2.3
9.6 2 2.8
8.6 2 2.4
47.9 ? 29.0
47.4 2 28.8
22.4 ? 7.6tt
28.2 ? 10.6
42.6 i- 18.4
40.5 i- 17.0
34.6 2 9.1
33.1 -t 11.8
22.8 2 10.2
24.9 t 12.2
14.3 2 9.1
21.7 t 12.8
28.0 2 13.8
31.0 ? 12.6
30.1 -C 24.5
18.0 ? 11.2
2.2 i- 2.1
2.3 2 1.9
2.0 i- 2.1
1.3 t- 0.92
1.4 2 0.76
1.0 2 0.50
4.1 2 2.7
3.1 ? 2.9
* Values are the mean i- SD. P values were Bonferroni corrected. For tumor necrosis factor a (TNFa)
and interleukin-lfl (IL-Ip) studies, cells were stimulated with heat-killed Staphylococcus epidetmidis (see
refs. 3 and 26). For IL-6 studies, cells were stimulated with 100 &nl
of concanavalin A. RA =
rheumatoid arthritis; G H = growth hormone; IGF-1
insulin-like growth factor 1; IGFBP-3 = IGF
binding protein 3. For further data, see ref. 26.
t P < 0.03 versus RA patients and versus elderly exercise controls, and P < 0.0005 versus elderly controls
(n = 7 young exercise controls).
$ P < 0.03 versus elderly exercise controls, and P < 0.005 versus elderly controls (n = 7 young exercise
controls).
3 P < 0.01 versus young exercise controls, and P < 0.05 versus elderly exercise controls.
8 P < 0.01 versus young exercise controls.
# P < 0.05 versus elderly controls.
* * P < 0.04 versus elderly exercise controls, and P < 0.01 versus RA patients.
tt P < 0.03 versus elderly exercise controls and RA patients.
not significant. There were no changes in leucine flux,
oxidation, or incorporation into protein synthesis as a
result of the training intervention.
When the use of methotrexate was examined in
the EL4 patients, those taking methotrexate (n = 4) had
significantly lower protein flux at both baseline and
followup than those not taking methotrexate ( P < 0.01)
(Figure IB). In fact, the rate of protein breakdown in the
patients taking methotrexate did not differ from that in
the young healthy subjects (66.9 2 4.7 versus 60.3 t- 3.3
pmoles/gm of total body potassium/hour; P = 0.45).
Moreover, the RA patients who were taking methotrexate had Significantly lower ESRs than those who were not
taking methotrexate (22.8 -t 8.1 mmhour versus 48.7 -t
29.2 mm/hour; P < 0.02). This supports the contention
that methotrexate leads to better control of inflammation than other medications. In contrast, prednisone did
not affect protein metabolism (Figure 1B) or ESR.
Hormone, blood glucose, and cytokine levels.
Hormone and cytokine production levels are presented
in Table 2. Baseline levels of IGF-1 were lower in elderly
control subjects than in young and elderly exercise
1121
PROTEIN METABOLISM IN RA AND AGING
Table 3. Multivariate linear regression models for leucine kinetic parameters at baseline and
after muscle strength training*
Dependent
variable
Independent
variable
Synthesis
Oxidation
Baseline glucagon
Baseline
GH
Glucagon
Followup
GH
Glucagon
Baseline TNFa
Followup GH
Flux
~
SE
P
(P)
Partial R2
P
-0.19
0.08
0.199
0.019
-6.65
0.12
1.97
0.06
0.315
0.204
0.002
0.042
-5.53
0.09
0.28
-0.13
1.96
0.04
0.10
0.04
0.250
0.157
0.222
0.261
0.009
0.041
0.011
0.006
~
’ There are no independent variables at followup for the dependent variable of synthesis. Data for
flux were log-transformed at followup. GH
=
subjects ( P < 0.05), and IGFBP-3 was lower in elderly
controls than young subjects (P < 0.05). There were no
between-group differences at baseline in the molar ratio
of IGF- MGFBP-3, plasma insulin or glucagon, or serum
cortisol. There were no changes in these parameters between baseline and followup among any of the subjects.
Production of IL-lp, TNFa, and IL-6 did not
change as a result of strength training (Table 2) (26). At
baseline, however, elderly exercisers and subjects with
RA produced -50% more total TNFa than did young
subjects (S epidermidzs-stimulated) ( P < 0.03), and
elderly control subjects produced -33% more than did
young subjects (P not significant). There were no betweengroup differences in the production of IL-1p or IL-6.
Determinants of leucine kinetics. Univariate linear regression was used to describe associations between
variables that are physiologically related to leucine oxidation, flux, and incorporation into protein synthesis.
Variables that were univariately associated with leucine
kinetics were then analyzed further using multivariate
regression (partial R2, Table 3). Subject groups were
combined to maximize statistical power, and when there
were differences between groups in terms of a particular
outcome variable, a “group” variable was added to the
regression model. The following independent variables
were candidates for testing in these models because of
significant univariate associations with the outcomes of
interest: IL-lp, TNFa, IL-6, the molar ratio of IGF-1/
IGFBP-3, plasma glucagon, glucose, insulin, serum cortisol, and the interaction of glucagon and insulin, glucagon and IL-lp, TNFa and IL-lp, and G H and the ratio
of IGF- 1/IGFBP-3.
Synthesis. Only plasma glucagon was a significant
predictor of leucine incorporation into protein synthesis,
accounting for -20% of the variability in protein synthesis (Table 3 and Figure 2). Consistent with glucagon’s
growth hormone; TNFa
=
tumor necrosis factor a.
role as a catabolic hormone, higher levels of plasma
glucagon were associated with lower rates of protein
synthesis (r = -0.45, P = 0.02).
Oxidation. Serum G H and plasma glucagon were
each significant predictors of leucine oxidation. Growth
hormone was inversely associated with oxidation, while
glucagon was directly associated. Together, GH and
glucagon accounted for 51% of the variability in leucine
oxidation at baseline, and 40% at followup (Table 3).
200
r = -0.45, p = 0.02
C
E
B 150
aa
W
J1
100
5
50
O
0
10
20
30
40
50
60
I
70
Synthesis
(pmoles/gm TBIUhour)
Figure 2. Relationship between plasma glucagon and leucine incorporation into protein synthesis at baseline. R = rheumatoid arthritis
patients; Y = young exercise control subjects; E = elderly exercise
control subjects; C = elderly control subjects (see Patients and
Methods for details). TBK = total body potassium.
RALL ET AL
1122
150
1
I
r = 0.47, p = 0.01
R
‘
40
Y
I
1
I
1
I
50
60
70
80
90
I
1
100 110
Flux
(pmoles/gm TBWhour)
Figure 3. Relationship between tumor necrosis factor a (TNFa)
production (Stuphy/ococcus epldennidts-stimulated) and leucine flux at
baseline. Subject groups are the same as in Figure 2. Because there
were significant between-group differences in TNFa and leucine flux at
baseline, “group” was added to the multivariate model. TNFa was still
a significant predictor of flux with “group” in the model ( P = 0.01).
TBK = total body potassium.
Turnover flux). There were significant betweengroup differences in leucine flux at baseline, so an
indicator variable for group was included in the multivariate model. At baseline, TNFa was a significant
predictor of protein turnover, accounting for 22% of the
variability (Table 3). Increased TNFa production was
associated with increased protein breakdown (Figure 3).
No such association was seen between protein flux and
IL-lP or IL-6. Serum GH was a significant predictor of
flux at followup (inversely associated), accounting for
21% of the variability (Table 3).
DISCUSSION
The present results demonstrate for the first time
that adults with RA have increased protein breakdown
rates compared with both young and elderly healthy
individuals. Furthermore, these findings suggest that
endogenous GH, glucagon, and TNFa are important
mediators of protein metabolism whose interrelationships can be modulated by resistance training. Although
protein breakdown in the RA group decreased after
training, we did not attribute a change in either the
leucine kinetic parameters or any of the hormone or
cytokine levels to the strength training intervention per
se, because the group X time interaction term was not
significant.
This is the first report of protein metabolism in
patients with RA, and the first time that state-of-the-art
protein kinetic methods have been applied to a chronic
inflammatory condition. We have previously described a
loss of body cell mass and an increase in resting energy
expenditure (hypermetabolism) to be associated with an
increase in the production of IL-1P and TNFa in
patients with RA (3). Here, we report elevated postabsorptive protein breakdown rates, suggesting that inflammation, even in relatively well-controlled RA, is
associated with increased protein catabolism as well as
hypermetabolism. Leucine flux at baseline-a measure
of whole-body protein turnover, and in the fasting state,
equals protein breakdown-was directly associated with
TNFa production (Figure 3). TNFa production was
increased in patients with RA compared with controls in
this study and in our previous studies (2,3). These
findings suggest that elevated TNFa levels lead to
increased protein breakdown in patients with RA. We
hypothesize that elevated energy expenditure and protein turnover, mediated in part by TNFa in these
patients, leads to the reduced body cell mass which we
have previously described and termed rheumatoid cachexia ( 3 ) .
Protein breakdown in the 4 patients taking methotrexate was comparable to that seen in the control
subjects, and significantly lower than that seen in the
patients who were not treated with methotrexate. It is
intriguing to speculate that methotrexate may be effective in normalizing protein metabolism in RA; however,
larger studies of this question are needed in order to
reach such a conclusion. In contrast, we found no
differences in leucine flux among patients with RA
according to prednisone use. One of the advantages of
studying RA as a model of chronic inflammation is that
low doses of corticosteroids are generally used in its
treatment. Our patients who were taking prednisone (n
= 5 ) were taking a mean dosage of 7 mg/day. Our
finding of no difference in protein metabolism with
prednisone therapy is similar to our earlier finding that
prednisone did not influence body composition or energy expenditure in RA (3).
We found a strong inverse association between
GH and leucine oxidation at both baseline and followup,
yet no association with synthesis. These results suggest
that under the conditions of this study, GH appears to
primarily inhibit catabolic processes, rather than to
PROTEIN METABOLISM IN F U AND AGING
directly promote anabolism, as occurs when G H is
infused at pharmacologic doses (27-30). Glucagon,
which historically has been classified as a catabolic
hormone because of its elevation during catabolic conditions, was inversely related to protein synthesis at
baseline and directly associated with oxidation at both
baseline and followup. These data indicate that glucagon
and G H are also important regulators of protein metabolism in RA, as they are in healthy subjects.
We also found no changes in leucine kinetic
parameters, fat-free mass, or body cell mass as a result of
the training intervention, despite significant increases in
strength. These results are consistent with the recent
finding of Yarasheski et a1 (31), who found no difference
in whole-body protein turnover, synthesis, or catabolic
rates, or in body composition after 16 weeks of resistance training among elderly men, despite their increased strength. Nevertheless, there was an increase in
the fractional rate of muscle protein synthesis in their
study (31). Our results suggest that the metabolic derangements of RA, although profound, do not prevent
the successful use of resistance exercise to reverse
weakness.
In conclusion, adults with RA have increased
protein breakdown rates, contributing to the hypermetabolism and cachexia that we have previously described
among these individuals. Although progressive resistance training led to improved strength and functional
status in patients with RA and in controls, we saw no
changes in protein metabolism or hormone levels as a
result of the training intervention among any of the
groups of subjects. This study also provides evidence
that endogenous levels of GH, glucagon. and TNFa
correlate with protein metabolism, and that these relationships are disturbed in patients with RA. Finally, the
occurrence of metabolic abnormalities even in wellcontrolled RA, albeit in a small group of patients,
suggests that attention to the nutritional status of patients with RA is warranted.
ACKNOWLEDGMENTS
T h e authors thank Dr. Joseph G. Cannon for advice
and support; Arlene Tenney for assistance with recruitment;
the staff of the Nutrition Evaluation Laboratory; members of
t h e Physiology and Body Composition Laboratories; and the
nursing staff of the Metabolic Research Unit a t the Jean Mayer
Human Nutrition Research Center o n Aging for dedicated
assistance. We also thank the volunteers who participated in
this study. This work is dedicated to the memory of the late
Rebecca Roubenoff.
1123
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