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J Appl Physiol 105: 859-867, 2008. First published July 17, 2008; doi:10.1152/japplphysiol.90655.2008
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TNF promoter polymorphisms associated with muscle phenotypes in humans

Dongmei Liu,1 E. Jeffrey Metter,2 Luigi Ferrucci,2 and Stephen M. Roth1

1Department of Kinesiology, School of Public Health, University of Maryland, College Park; and 2Clinical Research Branch, National Institute on Aging, Harbor Hospital, Baltimore, Maryland

Submitted 15 May 2008 ; accepted in final form 17 July 2008


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Tumor necrosis factor-{alpha} (TNF-{alpha}) is a potent catabolic factor to skeletal muscle. Single-nucleotide polymorphisms (SNPs) in the promoter region of the TNF-{alpha} coding gene, TNF, have been implicated in the interindividual variation in TNF-{alpha} production via transcriptional regulation. The present study investigated the association of muscle phenotypes with five TNF promoter SNPs, which potentially have biological significance. Female and male volunteers (n = 1,050) from the Baltimore Longitudinal Study of Aging were genotyped, and their regional and total body muscle mass, and arm and leg muscle strength were measured. Results indicated that putative high-expression alleles at positions –1031 and –863, individually or in combination in the haplotype 1031C-863A-857C-308G-238G, were associated with lower muscle mass in men. Specifically, carriers of –1031C, compared with noncarriers, exhibited lower arm muscle mass (6.4 ± 0.1 vs. 6.8 ± 0.1 kg, P = 0.01) and appendicular skeletal muscle mass (ASM) (24.3 ± 0.4 vs. 25.4 ± 0.2 kg, P = 0.02), with leg muscle mass and the ASM index (ASMI; kg/m2) also tending to be lower (P = 0.06 and 0.07). Similarly, –863A allele carriers (linked with –1031), compared with noncarriers, exhibited lower arm muscle mass (6.4 ± 0.1 vs. 6.8 ± 0.1 kg, P = 0.04). Carriers of the haplotype 1031C-863A-857C-308G-238G, compared with noncarriers, exhibited lower arm muscle mass (6.3 ± 0.2 vs. 6.8 ± 0.1 kg, P < 0.01), trunk muscle mass (25.7 ± 0.5 vs. 26.9 ± 0.3 kg, P < 0.05), and ASM (24.1 ± 0.5 vs. 25.3 ± 0.2 kg, P < 0.025), with tendencies for lower leg muscle mass and ASMI (P = 0.07 and 0.08). Results indicate that genetic variation in the TNF locus may contribute to the interindividual variation in muscle phenotypes in men.

genetics; skeletal muscle; inflammation; cytokine; tumor necrosis factor-{alpha}

THE LOSS OF MUSCLE MASS and strength with age, termed sarcopenia, has significant implications for physical and social well-being: it has been associated with a decline in mobility (27), impaired balance and increased risk of falls (45), physical disability (21), and morbidity (23), as well as mortality (31). Data from the Third National Health and Nutrition Examination Survey indicated that ~45% of the older population is sarcopenic with a healthcare cost of ~1.5% of the total healthcare expenditures for the year 2000 in the United States (22). Although the pathophysiological mechanisms underlying sarcopenia remain elusive, there is a growing consensus that sarcopenia is a multifactorial condition resulting from withdrawal of, or resistance to, several anabolic stimuli to muscle, including loss of central nervous system input, declining growth hormone, estrogen and testosterone, inadequate dietary protein and caloric intake, decreasing physical activity, muscle resistance to insulin and certain amino acids (9, 32), and development of several catabolic stimuli (40), such as inflammatory cytokines, IL-1β, TNF-{alpha}, and IL-6.

Aging is accompanied by a two- to fourfold increase in plasma levels of inflammatory mediators, including TNF-{alpha}, IL-6, interleukin 1 receptor antagonist (IL-1Ra), soluble TNF-{alpha} receptor (sTNFR), acute phase proteins such as C-reactive protein (CRP), and neutrophils (8). This low-grade inflammation may play an important role in age-related diseases such as Alzheimer's disease, atherosclerosis, Type 2 diabetes, and osteoporosis, as well as sarcopenia (8). In the elderly, skeletal muscle mass and strength have been inversely associated with circulating levels of IL-6 and TNF-{alpha} (49); the muscle atrophic response to strength training has been inversely related to baseline levels of sTNFR-I (7); and a lower muscle protein synthesis rate has also been associated with increased levels of sTNFR-II (46).

According to some authors, TNF-{alpha} is the driving force behind many age-related inflammatory changes, whereas other cytokines, like IL-6, IL-1Ra, sTNFR, as well as acute-phase proteins (APPs) like CRP, reflect responses to upregulated local or generalized TNF-{alpha} activity (5, 39). A strong catabolic effect of TNF-{alpha} on muscle has been well documented: TNF-{alpha} was originally designated as "cachectin" in recognition of its catabolic property and is one of the main signals that leads to muscle wasting associated with chronic diseases such as cancer, AIDS, congestive heart failure, chronic obstructive pulmonary disease (COPD), and rheumatoid arthritis (37).

The capacity to produce cytokines, including TNF-{alpha}, differs among individuals, as assessed by ex vivo stimulation (10), which may be ascribed to polymorphisms within the regulatory regions or signal sequences of cytokine genes (25). The TNF-{alpha} gene (TNF) is located on chromosome 6p21.3, which is within the highly polymorphic major histocompatibility complex (MHC) region of the human genome (17). Many single-nucleotide polymorphisms (SNPs) and microsatellites have been identified in the TNF locus, and the ones in the promoter region of TNF are thought to influence TNF transcription rate and likely have direct functional significance in regulating TNF-{alpha} production (41). In the promoter, five SNPs at positions (relative to the transcription start site) –1031T/C (rs1799964), –863C/A (rs1800630), –857C/T (rs1799724), –308G/A (rs1800629), and –238G/A (rs361525) have been well characterized. They have been shown to influence gene expression (17) and been linked to various infectious and autoimmune diseases (20) and age-related diseases (6), as well as longevity (29), although lack of association has also been reported (24, 51). It is believed that the interaction between nuclear proteins and these TNF SNPs is an important pathway for the allele-specific modulation of TNF expression (17).

Despite the evidence indicating that inflammatory factors including TNF-{alpha} play an important role in the genesis of sarcopenia and the importance of genetic variation in regulation of TNF expression, sarcopenia has not been studied in relation to genetic polymorphisms in the TNF promoter. The objectives of this study were to test the hypotheses that TNF promoter polymorphisms are significantly associated with muscle phenotypes in healthy people, 20–97 yr old, and that TNF promoter SNPs are significantly associated specifically with sarcopenia in people who are 55 yr old or older.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Subjects.   The subjects consisted of 1,050 adult men and women (20–97 yr of age) from the Baltimore Longitudinal Study of Aging (BLSA). Most participants of the BLSA are of European descent, healthy, and well educated (42). Subjects visited the Gerontology Research Center for medical, psychological, and physiological testing, which included assessment of muscle mass and strength. All BLSA participants provided written informed consent to participate in both direct and ancillary studies related to their collected data. The experimental protocols were approved by the Institutional Review Boards (IRB) for Medstar Research Institute, Johns Hopkins Bayview Medical Center, and the University of Maryland.

Potential confounders.   Based on previous studies, several factors that predict muscle mass and/or strength, and/or are associated with TNF-{alpha} production, were identified and included in the analyses. Body weight and height were measured to the nearest 0.1 kg and 0.5 cm, respectively, with a Detecto medical beam scale. Age was included as a covariate in the statistical analysis. Subjects were classified into three race groups: white, black, and other, which included all nonwhite and nonblack individuals. Tobacco smoking was evaluated by using a standardized questionnaire. Smoking habits were evaluated in three groups: current smoker, former smoker, and never smokers. Menopausal status and hormone replacement therapy (HRT) status were collected from female subjects. Medical history was assessed on each visit. Heart disease, diabetes mellitus, and cancer were recorded as "has ever had" or "never." Body fatness was obtained from dual-energy X-ray absorptiometry (DXA; see below). Details regarding measurement of these factors and subject exclusion criteria have been reported elsewhere (28, 30).

Measurements of skeletal muscle mass.   Total body fat (fat mass; FM) and soft tissue fat-free mass (FFM) measures were assessed by DXA (model DPX-L Lunar Radiation, Madison, WI) using previously described methods (28). Lean soft tissue mass has been used previously as a valid indicator of muscle mass (50). The scanner was calibrated daily before testing. Reliability has been assessed by performing two total body scans, 6 wk apart, on 12 older men (>65 yr old), and the difference between the two scans was ~0.01% for both FM and FFM. The appendicular skeletal muscle mass (ASM) was calculated as the sum of the lean soft tissue masses for both arms and legs (15). The limbs were isolated from the trunk by using DXA regional computer-generated lines with manual adjustment. With the use of specific anatomic landmarks, the legs were defined as the soft tissue extending from a line drawn through and perpendicular to the axis of the femoral neck and angled with the pelvic brim to the phalange tips, and the arms were defined as the soft tissue extending from the center of the arm socket to the phalange tips. The system software provides the total mass, FM, and fat- and bone mineral-free soft tissue mass for the total body and isolated regions. The fat and bone mineral-free portion of the extremities were assumed to represent ASM along with a small and relatively constant amount of skin and underlying connective tissues (15). The ASM index (ASMI) was calculated as ASM/height2.

Measurements of skeletal muscle strength.   Five indicators of muscle strength were measured: isometric hand-grip strength (grip), isokinetic knee extension peak torque at 30°/s (knee isokinetic 30°/s), and 180°/s (knee isokinetic 180°/s), isometric knee extension peak torque at angles of 120° (knee isometric 120°) and 140° (knee isometric 140°). Grip strength (Grip) was measured using the Smedley hand-held dynamometer (Stoelting, Wood Dale, IL). The dynamometer was adjusted individually for hand size, and three trials were performed for each hand. For the present study, the maximum strength obtained for the right hand was used as the measure of grip strength. Knee extension strength represented by peak torque (PT) was measured using the Kinetic Communicator dynamometer (Kin-Com model 125E, Chattanooga Group, Chattanooga, TN). For the dominant knee extensors, shortening PTs were measured at angular velocities of 30°/s and 180°/s, and static PTs were measured at the angle of 120° and 140°. The terms "shortening" and "lengthening" were substituted throughout the present study for the more commonly used terms "concentric" and "eccentric," respectively, based on the recommendations of Faulkner (12). For each test, subjects performed three maximal efforts, separated by 30-s rest intervals, from which the highest value of the three trials was accepted as the PT. PT was assessed by using the Kin-Com computer software (version 3.2). Detailed procedures regarding subject positioning and stabilization, gravity correction, and Kin-Com calibration are described elsewhere (28, 30). Briefly, subjects were positioned sitting with the backrest at an angle of 105°, with the hip angle between 80 and 85°, and were stabilized by using chest, waist, and thigh straps. The rotational axis of the dynamometer was aligned with the lateral femoral epicondyle and the resistance pad positioned just proximal to the lateral malleolus of the ankle joint. The Kin-Com angle reading was calibrated to the anatomic joint angle measured by a goniometer. Gravity corrections to torque were based on leg weight at 170° and calculated by the gravity correction program in the Kin-Com software package (version 3.2). The acceleration/deceleration rate was set at low; the activation force (i.e., force threshold required for movement of the dynamometer arm) was set at 20 N.

Genotyping and haplotype construction.   In this study, a total of five SNPs were genotyped in the TNF gene, including rs1799964/T-1031C, rs1800630/C-863A, rs1799724/C-857T, rs1800629/G-308A, and rs361525/G-238A. Blood samples (10 ml) were obtained from all individuals by using standard procedures, and genomic DNA was prepared from the EDTA-anticoagulated whole blood samples by standard salting-out procedures (Puregene DNA Extraction, Gentra Systems). Genotyping was done using TaqMan allele discrimination assays. All experiments were performed using the Applied Biosystems 7300 Real-Time PCR system. Each well of a 96-well optical reaction plate contained 6.25 µl 2x TaqMan Universal PCR Master Mix (Perkin-Elmer, Applied Biosystems Division), 0.625 µl of 20x TaqMan SNP mix, 1.5 µl (10–20 ng) of genomic DNA, and 4.125 µl DNase-free water. In addition to experimental samples, each plate contained two "no-template" controls and six positive controls (2 for each genotype). The genotypes of the positive control samples were validated by direct sequencing. Two different fluorescent dyes (FAM and VIC) were utilized to identify the alleles of interest. The PCR was done using 10 min at 95°C (AmpliTaq Gold Enzyme activation) and 40 cycles of 15 s at 92°C (denaturation) and 1 min at 60°C (annealing and extension). Analysis of raw data to determine genotypes was performed by the ABI 7300 Sequence Detection System software.

Haplotypes were constructed based on the population genotypes for five TNF SNPs using PHASE software (v2.1) (44). An input dataset was prepared, and the program was run according to the documentation for PHASE, version 2.1 (44). The haplotypes with frequencies of 5% and above were analyzed for their association with muscle phenotypes.

Sarcopenia identification.   Cutoff values for sarcopenia were used to divide the subjects of ages 55 yr old and older into sarcopenic and nonsarcopenic groups as follows: relative ASM index (ASMI = ASM/height squared) of <7.26 kg/m2 in men and <5.45 kg/m2 in women were considered sarcopenic based on the work of Baumgartner et al. (2). Sarcopenia defined using this approach has been associated with self-reported physical disability (2) and instrumental activities of daily living disability in the elderly (3).

Statistical analysis.   Hardy-Weinberg (H-W) equilibrium was determined for the five TNF SNPs by using a {chi}2 test to compare the observed genotype frequencies to those expected under H-W equilibrium. Pairwise linkage disequilibrium of five TNF SNPs, and race and sex differences for genotype and allele frequencies were assessed by {chi}2 test, and the Fisher's exact test was used when the sample size for any cell was 5 or fewer. Subjects' characteristics including muscle mass and muscle strength were compared between women and men using independent t-tests. Pairwise correlations between continuous variables were assessed by Pearson's correlation coefficients.

Since men and women differed on almost all variables studied, genotype-phenotype association studies were performed separately by sex. Eleven muscle phenotypic traits were included as outcome variables in the study: four muscle mass measurements [lean soft tissue mass of both arms, both legs, the trunk, and the total body (FFM)]; five muscle strength measurements [right hand isometric grip strength, knee extensor isokinetic peak torques at speeds of 30°/s (knee isokinetic 30°/s) and 180°/s (knee isokinetic 180°/s), knee extensor isometric peak torques at the angles of 120° (knee isometric 120°) and 140° (knee isometric 140°)]; and two derived muscle mass indicators (ASM and ASMI). Muscle traits were analyzed in all statistical analyses as continuous variables. Normality of each quantitative trait was confirmed by the Shapiro-Wilk test (W > 0.9 and P < 0.05).

Analysis of covariance (ANCOVA) was used to test the association between TNF promoter genotype/haplotypes and muscle phenotypes for each sex. In ANCOVA, muscle mass and strength measures were the response variables modeled one at a time; the categorical explanatory variables were genotypes/haplotypes and race; and each SNP and haplotype was analyzed independently of each other. The model was developed to make adjustment for the effects of age, body height, and total body fat, as well as regional muscle mass in the analyses of muscle strength; additional control was also considered for smoking status and chronic diseases, as well as menopause status and use of HRT in women. The quadratic term of age (age x age) was included in the model only when significant. Genotype/haplotype-by-race interaction was included in the model, and if significant, preplanned comparisons with Bonferroni adjustment were then made between genotype groups for race-stratified subgroups.

Physical characteristics between men/women with sarcopenia (sarcopenic group) and those with normal ASMI values (normal group) were compared using t-tests. Binary logistic regression was used to examine whether genotype or haplotype is a significant predictor for sarcopenic status (presence or absence of sarcopenia) in the older participants after controlling for multiple confounding variables consisting of race, sex, age, height, and FM. The Statistical Analysis Software System (SAS version 9.1, SAS Institute, Cary, NC) was used for statistical analysis. The {alpha} level to declare an effect significant was set at 0.05.

Statistical power for this study was estimated a priori as follows for the sex-specific analysis. Except for –238 G/A (which had a low frequency for the rare allele and thus low power estimates for most of the muscle phenotype measurements), for each SNP, statistical power to detect a 4% difference for muscle mass and a 6% difference for muscle strength between genotype groups ranged from 60% to 90% depending on the genotype frequencies and the SEs of muscle mass and muscle strength measurements. Power estimates were necessarily lower for subgroup analyses (e.g., sex x race) given the smaller sample sizes, and those findings should be considered preliminary.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
A total of 1,050 subjects were genotyped for TNF promoter SNPs, and the subject characteristics are presented in Table 1. Men were older and had higher weight, height, BMI, and FFM measures than women (P < 0.01); women had higher FM than men (P < 0.01; Table 1).


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  		Table 1. Physical characteristics of subjects by sex

 
Allele and genotype frequencies.   The allele and genotype frequencies for the five TNF SNPs are presented in Table 2. No significant deviation from H-W equilibrium was detected for any of the five TNF SNPs (P = 0.2–0.9). The genotype frequencies for variant allele homozygotes were low (n = 1–25 for each sex), so they were combined with the heterozygotes into one group as variant allele carriers for all five SNPs in the subsequent data analyses.


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  		Table 2. Observed genotype and allele frequencies for TNF promoter polymorphisms

 
The pairwise linkage disequilibrium of the five TNF promoter SNPs was assessed, and strong allelic association was detected between the –863C/A and the –1031T/C polymorphisms (R2 = 0.48, P < 0.001). Genotype frequencies were compared between two major race groups, whites and blacks, and only the genotypes of the SNP –857C/T differed in distribution in two race groups with the variant allele T being less represented in blacks than in whites (5.2% vs. 11.8%, P < 0.01). No significant sex difference in genotype distribution was detected for any SNP (P > 0.05) (data not shown).

Muscle mass, strength, and TNF promoter polymorphisms.   In women, no significant difference for any muscle mass measure was found between genotype groups of any SNP. Knee extensor isokinetic peak torque at 30°/s and isometric peak torques at 120° and 140° were significantly associated with –863C/A (P = 0.01–0.02, Table 3); compared with wild-type allele homozygotes, variant allele A carriers had higher leg muscle strength. Further controlling for leg muscle mass augmented the association between –863C/A and leg muscle strength (P = 0.01–0.03), suggested that the association between leg muscle strength and –863C/A in women was independent of muscle mass. No significant difference in any muscle phenotypic measure was found for the SNPs –857C/T, –308G/A, or –238G/A. A significant race interaction with –238G/A was found for leg lean mass, ASM, and ASMI (P < 0.05) in women; however, comparisons between genotype groups in either black or white women showed no significant difference in muscle mass values (data not shown).


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  		Table 3. Adjusted means for muscle mass and strength by TNF genotype in women

 
In men, significant genotypic associations of –1031T/C and –863C/A were found with muscle mass, but not with muscle strength. The allele C at position –1031 was significantly associated with lower arm lean mass and ASM (P = 0.005, 0.020), and carriers of C allele showed a nonsignificant tendency to exhibit lower leg lean mass and ASMI (P = 0.06, 0.07; Table 4). The allele A at position –863 was significantly associated with lower arm lean mass (P = 0.041), and carriers of A allele showed a nonsignificant tendency to exhibit lower ASM (P = 0.081; Table 4). Interaction of race with –1031T/C was found to be statistically significant for grip strength (P = 0.04), and this interactive effect was stronger after controlling for arm lean mass (P = 0.01). Race-stratified comparisons revealed that the association between –1031T/C and grip strength was accounted for by the association present in black men, with black men carrying variant allele C being significantly higher in grip strength than T allele homozygotic black men (42.2 ± 1.7 vs. 36.8 ± 1.0 kg; P = 0.007). No significant relationship was found between muscle phenotypes and TNF promoter SNPs at positions –857, –308, and –238 (data not shown).


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  		Table 4. Adjusted means for muscle mass and strength by TNF genotype in men

 
Haplotypes.   Seventeen TNF promoter haplotypes were constructed using PHASE software (v. 2.1) based on the genotype data for the five TNF promoter SNPs. Five haplotypes with frequencies approaching or over 5% were assessed for association with muscle mass and muscle strength, including –1031C-863C-857C-308G-238A (CCCGA, 4.8%), –1031T-863C-857T-308G-238G (TCTGG, 7.9%), –1031C-863A-857C- 308G-238G (CACGG, 13.8%), –1031T-863C-857C-308A-238G (TCCAG, 16.2%), and –1031T-863C-857C-308G-238G (TCCGG, 50.3%). For purposes of clarity, the TCCGG haplotype is referred to as the "wild-type haplotype," and the other four haplotypes are referred to as "variant haplotypes." Few subjects were homozygous for the four variant haplotypes, so homozygotes for any variant haplotypes were combined with subjects heterozygous for the corresponding variant haplotypes into variant haplotype carrier groups.

TNF promoter haplotype and muscle mass and strength.   In women, no significant difference in muscle phenotypes was observed for any haplotype group pairs (data not shown). Significant interactions between race and haplotypes (except CACGG) were observed for various muscle mass and muscle strength, and comparisons within each race group appeared to suggest that in women the associations between TNF promoter haplotypes and muscle phenotypes were stronger in blacks than in whites and variant haplotypes were associated with inferior muscle phenotypes: in black but not white women, wild-type haplotype TCCGG was associated with lower leg muscle mass, lower ASM and ASMI, and lower grip strength and knee extensor isokinetic peak torque at 180°/s (P < 0.006) (Table 5). However, caution needs to be taken in interpreting the result because of low sample size for noncarriers of the wild-type haplotype in black women.


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  		Table 5. Race stratification analyses for 4 major TNF haplotypes and muscle phenotypes in women

 
In men, the CACGG haplotype was significantly associated with lower arm lean mass, trunk lean mass, and ASM (P = 0.008–0.048), and carriers of CACGG showed a nonsignificant tendency to exhibit lower leg lean mass and ASMI (P = 0.07 and 0.082, respectively; Table 6). Significant race interactions with haplotypes were also found for various muscle phenotypes, and comparisons within each race group showed that CACGG carriers were significantly higher in grip strength than noncarriers in black men (43.4 ± 2.3 vs. 37.4 ± 0.9 kg, P = 0.015) but not in white men.


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  		Table 6. Adjusted means of muscle mass and strength for carriers and noncarriers of 5 major TNF haplotypes in men

 
Sarcopenia.   In subjects 55 yr of age and older (297 women and 328 men), 61 women and 88 men were identified as sarcopenic. Comparison in characteristics between normal and sarcopenic subjects for each sex indicated that in both sexes, sarcopenic subjects were older, lower in weight, body mass index, FFM, all regional lean mass measures (arm, leg, trunk), ASM, and ASMI. No significant difference in the frequencies of TNF genotypes and haplotypes between sarcopenic and nonsarcopenic groups was observed in either women or men (P > 0.10, data not shown). Logistic regression analysis indicated that TNF promoter genotypes or haplotypes were not associated with sarcopenic status of the subjects even after controlling for sex, race, age, and FM (P > 0.36, data not shown).


   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
To our knowledge, our investigation is the first study attempting to evaluate the association between genetic polymorphisms in the TNF gene locus and muscle phenotypes in an adult population of various ethnic backgrounds. The most important finding was the association of the –1031C/–863A allele with lower muscle mass, especially muscle mass of the arms, in men. Both individually and as part of a haplotype, the –1031C/–863A alleles were consistently associated with lower muscle mass in men, which is consistent with the strong linkage disequilibrium observed for these two alleles. In general, the findings indicate that TNF promoter polymorphisms may moderate skeletal muscle traits, but no polymorphisms are exerting a strong effect, nor are any associated with sarcopenia defined using Baumgartner's approach (2), thus indicating TNF as a minor rather than major contributing gene for skeletal muscle traits.

TNF-{alpha} has been recognized as a potent catabolic factor, able to induce muscle wasting through direct and indirect pathways. Indirectly, TNF-{alpha} can induce anorexia and hypermetabolism (47), suppress expression of insulin-like growth factor-I (IGF-I) (14), and induce skeletal muscle insensitivity to insulin (4). Directly, TNF-{alpha} can affect protein transcription efficacy in skeletal muscle (26), can induce skeletal muscle protein breakdown by the ubiquitin/proteasome system via activation of nuclear factor-kB (NF-{kappa}B) (37), and can induce loss of myonuclei by apoptosis via interaction with TNFR1 (11). Elevated TNF-{alpha} mRNA and protein levels in skeletal muscle have been associated with lower muscle mass and/or strength in elderly people (16) and old animals (36). As suggested by Ferrucci and Guralnik (13), even transient elevations in TNF-{alpha} can inhibit the degree of protein synthesis over a relatively long period of time, which could ultimately lead to muscle frailty in older people.

The –863A allele in TNF has been indicated to be physiologically relevant, enhancing TNF-{alpha} expression in humans in some (18, 19) but not all studies (43). Higuchi et al. (18) found that the transcriptional promoter activity of the –1031C/–863A allele in response to concanavalin A (Con A) stimulation was 2.0-fold higher than that of the wild-type allele and that the levels of TNF-{alpha} production by Con A-activated peripheral blood mononuclear cells from the subjects with –1031C/–863A was 1.8-fold higher than that from noncarriers. Hohjoh et al. (19) suggested that allele-specific binding of nuclear factor OCT-1 with –863A could contribute to the modulation of TNF expression. Skoog et al. (43), however, found that –863A was functional but in the opposite direction such that the variant allele was associated with lower transcriptional activity and reduced circulating levels of TNF-{alpha} compared with the wild-type allele. Skoog et al. (43) discussed that use of different cell lines, constructs, and stimulants may yield contradictory results in similar reporter gene studies.

Given the catabolic nature of TNF-{alpha} in skeletal muscle, our study lends support to the hypothesis that men carrying –863A, which is associated with higher TNF transcriptional activity and higher basal production of TNF-{alpha}, exhibit lower muscle mass. These findings were not observed in women in the present study. Of course, lack of data on muscle gene expression and protein production prevents us from unraveling the mechanisms underpinning the relationship between muscle mass and TNF gene polymorphisms. We did not find any significant association between muscle phenotypes and TNF promoter SNPs at positions –857, –308, and –238. Reports regarding the functional relevance of these three SNPs and their associations with various diseases are inconclusive and contradictory (20).

Although muscle mass and muscle strength were correlated in the present study (r = 0.17–0.63, P < 0.05; Table 7), the genotypic associations of –1031C/863A with muscle mass and muscle strength were not reciprocally supportive. The association of –863C/A with muscle mass in men was not translated into an association with muscle strength, and its association with muscle strength in women was independent of muscle mass. We have no clear explanation for this disparity. The most likely explanation is the generally low correlation values observed for most subgroups for mass and strength phenotypes (Table 7), with only white men showing strong correlations. This may reflect noise in the data, or reduced accuracy of DXA in older individuals to accurately define FFM. Although speculative, a potential biological explanation is that TNF-{alpha} may have an effect on the central or peripheral nerve function independent of muscle tissue. TNF-{alpha} is a pleiotropic cytokine, with a broad range of effects on different cell types, including important roles in normal functioning and development of the central nervous system (CNS) and CNS pathology (33), which are beyond the scope of the present study. Further studies are needed to clarify the relationship between genetic variation in the TNF locus and muscle performance at the tissue level.


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  		Table 7. Correlations between regional lean soft tissue mass and limb muscle strength by race and sex

 
The genotype and phenotype associations found in our study have sex and race specificity. Regarding the sex specificity of our results, similar findings have been made by other studies. For example, Pedersen et al. (35) found that plasma level of TNF-{alpha} was associated with lower ASM (DXA) and body cell mass (total body potassium counting) in elderly men but not in elderly women. Roth et al. (38) found that genotype of another cytokine-encoding gene, interleukin-6 (IL6), was associated with FFM in men but not women; muscle strength was not associated with genotype in either men or women. There is limited information in the literature explaining this sex specificity. In the present study, although –863C/A was found to be associated with several leg muscle strength measurements in females, failure to observe a concordant relationship between muscle strength and SNP –1031T/C, which was in linkage disequilibrium with –863C/A, and between muscle strength and the haplotype of CACGG, which contains –863A, prevents us concluding an association between TNF promoter SNPs and muscle strength in women.

In the present study, significant interactive effects of race with TNF genotype and haplotype were extensively observed for muscle mass and strength in both women and men. Comparisons within race-stratified subgroups suggested a greater genotypic association in blacks than in whites. Unfortunately, the unbalanced design of the present study in terms of race makes the interpretation of these findings tentative. The race effect on the TNF promoter genotypic association with muscle phenotypes is in line with a previous study, in which Visser et al. (49) reported that the relationship between levels of TNF-{alpha} and IL-6 and muscle phenotypes were stronger in blacks than in whites: for each SD increase in TNF-{alpha} level, black men had a greater decrement in thigh muscle area than white men, and black women had a greater decrement in knee extensor strength than white women.

Combining adjacent SNPs into composite multilocus haplotypes has been proposed as a robust and powerful approach to the genetic study of a specific region because haplotypes, by taking into account the regional linkage disequilibrium information, are more informative than single SNPs (1). Haplotype profile composition and frequencies in the present study were similar to a previous study (48). We found that the –1031C and –863A-containing haplotype, CACGG, was significantly associated with lower muscle mass in men, which is consistent with the findings from our single SNP analysis that both –1031C and –863A were associated with lower muscle mass in men. The functional relevance of this haplotype has been previously suggested by Park et al. (34), who found that the CACGG haplotype was associated with an increased risk of Behcet's disease, a chronic multisystem inflammatory disorder of unknown etiology.

TNF-{alpha} has been implicated as a mediator of sarcopenia, so we explored the relationship between sarcopenia and TNF promoter genotypes in a subpopulation of adults who were 55 yr old or older. Our case-control analyses did not show any significant relationship between sarcopenic status and TNF genotypes or haplotypes. This negative result is not unexpected, since in the muscle mass analyses we found minimal genotypic effect on ASMI, on which sarcopenia in this study is based.

Our study is not without limitations. First, the BLSA participants are mainly healthy adults and may not be representative of the broad population. Second, only a small number of subjects finished a physical-activity questionnaire in this cohort, preventing its use as a covariate, although previous studies (28) on BLSA subjects indicated that only a very small percentage of subjects (<1%) participated in regular resistive exercise and there was no significant difference in participation by age or sex. Third, we did not have any measure on TNF-{alpha} expression or production. This limitation prevents us from clarifying the physiological relationship between the genotypes and the muscle phenotypes. Finally, our study is unbalanced in terms of race composition. The small sample size for blacks makes the study underpowered to address the interaction between race and genotype/haplotype for muscle phenotypes, so these findings should be considered preliminary.

In conclusion, SNPs in the promoter region of the TNF gene, which encodes the catabolic cytokine TNF-{alpha}, are associated with human skeletal muscle phenotypes in a sex-specific manner: putative high TNF-{alpha}-producing variant alleles at positions –1031 and –863 individually or in combination in the haplotype 1031C-863A-857C-308G-238G are associated with lower muscle mass in men but not in women. In addition to race, age, age x age, FM, and height, TNF promoter genotype/haplotype explained 1–2% of the variation in arm muscle mass in men. The findings support genetic variation in the TNF promoter as a minor contributor to interindividual variability in skeletal muscle phenotypes, but argue against TNF acting as a major contributor to these traits in general or to sarcopenia in particular.


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The BLSA research was conducted as a component of the Intramural Research Program of the National Institute on Aging. This work was further sponsored by National Institutes of Health Grants AG-021500 and AG-022791.


   FOOTNOTES
 

Address for reprint requests and other correspondence: S. M. Roth, 2134 SPH Bldg., Dept. of Kinesiology, School of Public Health, Univ. of Maryland, College Park, MD 20742-2611 (e-mail: sroth1{at}umd.edu)

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


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