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1 From the Department of Respiratory Medicine, University Hospital Maastricht, Netherlands (RB, EFW, and AMS); the School of Medicine, University of Southampton, Southampton, United Kingdom (RFG and WMH); the Section of Respiratory Medicine, Cardiff University, Cardiff, United Kingdom (DJS); and the Asthma Centre Hornerheide, Horn, Netherlands (ECC)
2 Supported by research grants from the British Lung Foundation, GlaxoSmithKline, and Numico Research BV. 3 Address reprint requests to R Broekhuizen, Department of Respiratory Medicine, University Hospital Maastricht, PO Box 5800, 6202 AZ Maastricht, Netherlands. E-mail: r.broekhuizen{at}pul.unimaas.nl.
ABSTRACT
Background: Cachexia is common in chronic obstructive pulmonary disease (COPD) and is thought to be linked to an enhanced systemic inflammatory response.
Objective: We investigated differences in the systemic inflammatory profile and polymorphisms in related inflammatory genes in COPD patients.
Design: A cross-sectional study was performed in 99 patients with COPD (Global Initiative for Chronic Obstructive Lung Disease stages II–IV), who were stratified by cachexia based on fat-free mass index (FFMI; in kg/m2: <16 for men and <15 for women) and compared with healthy control subjects (HCs). Body composition was determined by bioelectrical impedance analysis. Plasma concentrations and gene polymorphisms of interleukin 1ß (IL-1ß –511), IL-6 (IL-6 –174), and the tumor necrosis factor system (TNF- –308 and lymphotoxin- +252) were determined. Plasma C-reactive protein, leptin, and urinary pseudouridine (as a marker of cellular protein breakdown) were measured.
Results: Fat mass, leptin, and pseudouridine were significantly different (P < 0.001) between noncachectic patients (NCPs) and cachectic patients (CPs: n = 35); the systemic inflammatory cytokine profile was not. NCPs had a body compositional shift toward a lower fat-free mass and a higher fat mass compared with HCs. CPs and NCPs had a greater systemic inflammatory response (P < 0.05) than did HCs, as reflected in C-reactive protein, soluble TNF-R75, and IL-6 concentrations. The overall distribution of the IL-1ß –511 polymorphism was significantly different between the groups (P < 0.05).
Conclusions: In COPD patients, who are characterized by an elevated systemic inflammatory response, cachexia is not discriminatory for the extent of increase in inflammatory status. This study, however, indicates a potential influence of genetic predisposition on the cachexia process.
Key Words: Chronic obstructive pulmonary disease • COPD • body composition • inflammation • polymorphism • cachexia • protein breakdown • leptin
INTRODUCTION
Chronic obstructive pulmonary disease (COPD) is a lung disease characterized by irreversible chronic airflow limitation with or without alveolar wall destruction. Besides lung impairment, patients with COPD are progressively disabled by systemic impairment. Weight loss and particularly loss of fat-free mass (FFM) were shown to adversely affect respiratory and peripheral muscle function (1) and exercise capacity (2). In addition, low FFM is associated with impaired health status (3, 4) and an increased rate of mortality (5).
The disproportionate loss of FFM in COPD is often referred to as pulmonary cachexia. Cachexia has been defined as disproportionate cytokine-driven loss of skeletal muscle (6), which is reflected in loss of FFM. However, in human studies, in COPD as well as in other chronic diseases, the association between cachexia and systemic inflammation is equivocal. Although some studies report increased concentrations of inflammatory markers in cachectic patients (CPs) with COPD, other studies do not (7–9). This inconsistency is at least partly due to differences in the clinical definition of the cachexia syndrome used in studies which varies from involuntary weight loss to a low body mass index (BMI; in kg/m2) or a low FFM index (FFMI). In COPD, the precise relation between cachexia and systemic inflammation therefore remains to be determined. Understanding this relation is important for characterization and stratification of patients eligible for specific anabolic or antiinflammatory treatments and to monitor therapeutic outcome. Cytokines play a key role in the inflammatory process. The production of a cytokine is influenced by single base changes [single nucleotide polymorphisms (SNPs)], usually in the promoter region of its gene (10). Therefore, individuals may have a genetically determined propensity for raised amount of cytokine production.
Both cachexia and systemic inflammation could be influenced by genetic polymorphisms. In published reports, it was hypothesized that differences in polymorphisms of inflammatory cytokines may influence the cause of COPD (11–14). Genetic predisposition could also explain the typical differences in COPD phenotypes that were traditionally characterized as the "pink puffer" and the "blue bloater" and which showed striking differences in anthropometric features. However, no studies have been performed to investigate whether a link exists between SNPs in inflammatory cytokine genes and cachexia and systemic inflammation in COPD.
The aim of the present study was to characterize the systemic inflammatory profile of CPs relative to noncachectic patients (NCPs) with COPD and to healthy control subjects (HCs) and to study a possible modulatory role of SNPs in inflammatory cytokine genes.
SUBJECTS AND METHODS
Patients
One hundred two patients with stable COPD [stages II–IV as determined by the Global Initiative for Chronic Obstructive Lung Disease (15, 16)], free from exacerbation for 8 wk, were included from a Dutch white population for an intervention trial (17). Baseline measurements of this patient group were used and compared with 2 groups of HCs (see below). Patients with confounding diseases such as malignancies, gastrointestinal or kidney abnormalities, metabolic or endocrine diseases, and inflammatory diseases were excluded. Because of technical reasons, it was not possible to measure genotype in 3 patients; therefore, they were excluded from this study. The ethical review board of the University Hospital Maastricht approved the study, and all subjects, including the HCs, gave their written informed consent.
Healthy control subjects
Twenty healthy Dutch volunteers, matched for sex and age, were recruited by an advertisement in a local newspaper for baseline comparison of body composition, genotype, and inflammatory indicators. Genotypes of a larger healthy white population comprising 213 renal and bone marrow donors (RBMDs) from Southampton (ratio of men to women: 1:1) were also determined for comparison with the subjects' genotypes.
Pulmonary function
Forced expiratory volume in 1 s (FEV1) and forced vital capacity were calculated from the flow volume curve with the use of a spirometer (Masterlab; Jaeger, Würzburg, Germany). The highest value of at least 3 measurements was used. FEV1 was also calculated 15 min after inhalation of ß-agonist by a metered-dose inhaler. Diffusing capacity for carbon monoxide (DLCO) was determined by using the single-breath method (Masterlab; Jaeger). Lung functional indicators were expressed as percentage of reference values (18). Blood was drawn from the brachial artery while the patients were breathing room air or using their oxygen therapy when indicated. Arterial oxygen tension (PaO2) and arterial carbon dioxide tension were analyzed with a blood gas analyzer (ABL 330; Radiometer, Copenhagen, Denmark).
Body composition
BMI was calculated, and FFM (in kg) was estimated with the use of single-frequency (50 kHz) bioelectrical impedance analysis (Xitron Technologies, San Diego, CA), with subjects in a supine position as described by Lukaski et al (19). FFM of patients was calculated by using the disease-specific equation proposed by Schols et al (20), and FFM of control subjects was calculated by using the equations of Lukaski et al (19). FFMI was calculated as FFM (in kg) divided by height2 (in m). Patients were classified as cachectic when their FFMI was <16 for men and <15 for women. Fat mass (FM; in kg) was estimated as total body weight minus FFM.
Blood variables
For each subject, fasting blood was collected in evacuated blood collecting tubes containing EDTA (Becton Dickinson Vacutainer Systems, Plymouth, United Kingdom) in the early morning (0800–0900). After centrifugation twice at 1000 x g for 10 min at 4 °C within 2 h of collection, plasma samples for cytokines and peripheral blood mononuclear cells for DNA extraction were subsequently stored at –70 °C.
Cytokines
In plasma, interleukin 1 ß (IL-1ß), IL-6, and tumor necrosis factor (TNF-) were determined in duplicate by Quantikine high-sensitivity sandwich enzyme-linked immunosorbent assay (ELISA) kits (R&D Systems, Minneapolis, MN). Soluble TNF-R55 and sTNF-R75 were measured in duplicate by using the ELISA protocol as previously described by Leeuwenberg et al (21). Leptin concentrations were measured in duplicate by an in-house double antibody sandwich ELISA assay by using a monoclonal antibody specific for human leptin as described earlier (22). C-reactive protein (CRP) was assessed in duplicate by high-sensitivity particle-enhanced immunonephelometry (Dade Behring, Leusden, Netherlands) (23). Albumin was determined with the bichromatic digital endpoint method, with a Bromcresol purple reagent (Synchron LX20; Beckman Coulter, Los Angeles, CA).
Genotyping
The peripheral blood mononuclear cells were analyzed to determine SNPs for the TNF- –308 (TNF*1 and TNF*2), lymphotoxin (Lt-) +252 (TNFB*1 and TNFB*2), IL-6 –174 (IL6*1 and IL6*2), and IL-1ß –511 (IL1*1 and IL1*2) genotypes. Genomic DNA was extracted by a salting out procedure (24). Each SNP was detected by using a two-reaction amplification refractory mutation system–polymerase chain reaction approach based on previously published methods (25). Full details are described elsewhere (26, 27).
Pseudouridine
A morning urine sample was collected in which pseudouridine (PSU), which is a stable urinary end product of RNA turnover and hence a marker of cellular protein breakdown, was measured by HPLC (28). Values are reported as the ratio to urinary creatinine and were corrected for FFM.
Statistical analysis
Results are presented as means ± SDs for all variables that were normally distributed. Differences among the groups were analyzed by the Student's t test for independent samples. Differences in the distribution of the genotypes between groups were examined by using the chi-square test, or the Fisher's exact test when appropriate. The chi-square test was corrected for multiple comparisons when appropriate, showing both the uncorrected and the more conservative corrected P values. Differences in cytokine concentrations among the different genotypes were determined by one-factor analysis of variance. Genotype frequencies for each SNP were tested for agreement with Hardy-Weinberg equilibrium by comparing with expected values calculated from allele frequencies. Data were analyzed with SPSS (Statistical Package for the Social Sciences, version 11.0 for Windows; SPSS Inc, Chicago, IL). P values < 0.05 were considered significant.
RESULTS
Stratification of patients with COPD by cachexia (Table 1) showed that DLCO was more compromised in CPs (42 ± 18% predicted) than in NCPs (54 ± 20% predicted; P = 0.024), but no significant differences in age, FEV1, long-term oxygen therapy, smoking history, and resting PaO2 were observed. However, arterial carbon dioxide tension was higher in CPs (5.66 ± 0.95 kPa) than in NCPs (5.26 ± 0.64 kPa; P = 0.030). Inflammatory markers were not significantly different between CPs and NCPs. Cytokine analysis also showed that patients with COPD had higher concentrations of sTNF-R75, CRP, and IL-6 than did the HCs (P < 0.001). Albumin was significantly lower in CPs than in NCPs (P = 0.032; Table 1). IL-1ß could not be detected.
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TABLE 1. Characteristics of cachectic patients (CPs), noncachectic patients (NCPs), and healthy control subjects (HCs)1
The body composition of patients stratified by cachexia and age- and sex-matched HCs is shown in Figure 1. By definition, CPs had a lower FFMI than did the NCPs and HCs (CPs: 14.2 ± 0.9; NCPs: 16.9 ± 1.7; HCs: 20.2 ± 2.6; P < 0.001 for all). CPs also had a lower BMI than did the NCPs and HCs [CPs (19.0 ± 2.2) compared with NCPs (24.2 ± 3.2), P < 0.001; CPs compared with HCs (25.7 ± 2.8), P < 0.001]. The fat mass index (FMI) was lower in the CPs (4.9 ± 1.7) than in the NCPs (7.3 ± 2.4; P < 0.001) but was higher in the HCs (5.5 ± 2.4) than in the CPs (P = 0.852). BMI did not differ significantly between HCs and NCPs (P = 0.137), but the FFMI was lower (P < 0.001) and the FMI was higher (P = 0.006) in the NCPs than in the HCs.
FIGURE 1.. Mean (±SEM) fat-free mass index (FFMI) and fat mass index (FMI) in cachectic patients (CPs; n = 35), noncachectic patients (NCPs; n = 64), and healthy control subjects (HCs; n = 20). Means with different lowercase letters are significantly different, P < 0.01 (one-way ANOVA with Bonferroni correction).
Besides the observed difference in FM between patients stratified for cachexia, leptin was also significantly different, both absolutely [CPs (2.94 ± 3.06 ng/mL) compared with NCPs (9.99 ± 11.40 ng/mL), P = 0.002; CPs compared with HCs (9.94 ± 11.26 ng/mL), P = 0.033; NCPs compared with HCs, P = 1.000] and when corrected for FM] CPs (0.19 ± 0.16 ng · mL–1 · kg–1) compared with NCPs (0.42 ± 0.40 ng · –1mL · kg–1), P = 0.024; CPs compared with HCs (0.58 ± 0.66 ng · –1mL · kg–1), P = 0.003; NCPs compared with HCs, P = 0.366] (Figure 2). PSU, which is associated with active tissue breakdown, was highest in CPs (50.6 ± 11.8 µmol/mmol), intermediate in NCPs (43.0 ± 10.4 µmol/mmol), and lowest in HCs (36.5 ± 6.2 µmol/mmol) (CPs compared with NCP: P = 0.003; CPs compared with HCs: P < 0.001; NCPs compared with HCs: P = 0.061). This difference was more pronounced when PSU was corrected for FFM [CPs (1.28 ± 0.37 µmol · mmol–1 · kg–1) compared with NCPs (0.91 ± 0.32 µmol · mmol–1 · kg–1), P < 0.001; CPs compared with HCs (0.62 ± 0.23 µmol · mmol–1 · kg–1), P < 0.001; NCPs compared with HCs, P = 0.004] (Figure 2).
FIGURE 2.. Mean (±SEM) urinary pseudouridine corrected for fat-free mass (PSU/FFM) and leptin corrected for fat mass (leptin/FM) in cachectic patients (CPs; n = 35), noncachectic patients (NCPs; n = 64), and healthy control subjects (HCs; n = 20). Means with different lowercase letters are significantly different, P < 0.05 (one-way ANOVA with Bonferroni correction).
The distribution of genotypes among CPs, NCPs, HCs, and RBMDs from Southampton is shown in Table 2. A significant overall difference in distribution of the SNP at –511 in the IL-1ß gene was seen (P < 0.01). This was due to a significant difference between CPs and RBMD control subjects from Southampton (P < 0.006). However, because of the small sample size in some groups, differences between the other groups could not be pinpointed: CPs compared with NCPs (P = 0.174) and CPs compared with age-matched HCs (P = 0.096) with a Bonferroni correction factor of 6. The distribution of IL-1ß –511 genotypes fitted Hardy-Weinberg equilibrium in the NCPs, age-matched HCs, and RBMD Southampton HCs but not in the CPs.
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TABLE 2. Genotype distribution in cachectic patients (CPs), noncachectic patients (NCPs), healthy control subjects (HCs), and renal and bone marrow donor (RBMD) subjects1
No significant differences were observed in distribution of genotypes of the other inflammatory cytokine genes between patients with COPD and HCs. No significant differences were seen in polymorphism distribution between the healthy Dutch control group and the HCs from Southampton, although the distribution of the SNP at –308 of the TNF- and the SNP at +252 of the Lt genes in the Southampton HCs did not fit the Hardy-Weinberg equilibrium. No relation was observed between plasma concentrations of proinflammatory cytokines and polymorphisms in the genes that code for these markers in patients or control subjects (data not shown).
DISCUSSION
In a group of patients with COPD characterized by systemic inflammation, the presence of cachexia did not relate to the severity of the systemic inflammatory response. However, a substantial difference was found in the distribution of the IL-1ß –511 SNP between CPs and RBMD HCs.
The FFMI-based definition of cachexia used in this study not only discriminated for a low FFMI but also for low FM on a group level. In addition, cachexia discriminated for 2 different biochemical markers that are related to body composition. PSU, which is a stable urinary end product of RNA turnover and hence a marker of cellular protein breakdown, is related to muscle mass. In agreement with a previous study (29), PSU was higher in CPs than in NCPs, even after correction for FFM. This could be a reflection of increased muscle breakdown in CPs with COPD. It is hypothesized that the increase in protein breakdown coincides with an increase in protein synthesis (30), reflecting an inflammation-induced redirection of muscle protein in favor of synthesis of acute-phase proteins (31). However, further studies are needed to clarify this issue by measuring, for instance, acute-phase protein turnover in patients with COPD stratified according to the presence or absence of cachexia.
The second biochemical marker, leptin, which is a pleiotropic cytokine produced by fat tissue, was disproportionately lower in CPs than in NCPs when corrected for the amount of FM. Excessively low leptin concentrations have also been found in patients with chronic heart failure with cachexia (32). In that study, the investigators hypothesized that low leptin concentration could be caused by an overactivation of the sympathetic nervous system found in CPs with heart failure. ß3 Adrenoceptor activation was indeed shown to decrease leptin (33). In COPD, Takabatake et al (34) have linked the loss of circadian rhythm of circulating leptin, which is normally coupled to the activity of the autonomous nervous system, to pathophysiologic features in COPD. From reports on abnormalities of hypothalamic-pituitary function in hypoxemic patients with COPD (35), Takabatake et al (34) speculated that low leptin concentration and the blunted diurnal variation in leptin could cause an alteration in the negative feedback to the hypothalamic-pituitary axes. In the present study, the CPs were not characterized by a lower resting PaO2 but had lower values for DLCO as a hallmark of emphysema. Studies have shown that exercise-induced oxygen desaturation, indicative for the presence of intermittent hypoxia, is inversely related to the DLCO (36).
The increased systemic inflammatory response observed in the patients of the present investigation confirms other studies in comparable populations with COPD (37, 38). In contrast to some studies, we did not find differences in inflammatory markers between patients with or without cachexia. Several studies relate inflammatory markers to FFM with the use of different methods. Patients with COPD with low creatinine-height index (CHI), a urinary marker of FFM, had higher concentrations of TNF-, IL-6, and their receptors than patients with normal CHI (8). However, CHI was determined by using urinary creatinine nitrogen excretion, which is an indirect marker for skeletal muscle depletion. In addition, subjects did not receive standard meals, and no correction was made for differences in nitrogen consumption of protein-rich products such as meat (8). In contrast, using midthigh muscle cross-sectional area for stratification, Debigaré et al (9) reported no difference in IL-6 concentrations.
Remarkably, the NCPs also had a compromised body composition, as indicated by a depleted FFM and a higher FM, relative to the HCs. In elderly subjects without disease, sarcopenia, which is a decrease in muscle mass that does not necessarily coincide with weight loss, is related to increased systemic inflammation, especially to IL-6 (39, 40). These findings could imply that the NCPs have accelerated sarcopenia. This suggests a more gradual process in the cause of pulmonary cachexia, first depleting FFM and in later stages also FM. Inflammation could be a trigger for the body compositional shift, and in more advanced disease stages other factors could either enhance this process or specifically affect FM.
Differences in concentrations of inflammatory markers could be a consequence of differences in inflammatory gene polymorphisms. To explore this possibility, we studied the polymorphisms of the genes that encode for TNF-, IL-1, and IL-6. No significant differences in TNF- –308, LT +252, and IL-6 –174 were found between patients with COPD and HCs. This finding agrees with other studies in white subjects (11, 13, 14, 41, 42) and of some in Asian subjects (12). To our knowledge, this is the first study on IL-6 –174 distribution as well as on the possible relation between inflammatory cytokine gene polymorphisms and cachexia in COPD.
We found a significant difference in distribution of IL-1ß –511 polymorphisms between CPs and healthy RBMDs. A few studies investigated IL-1ß –511 polymorphism in COPD. Ishii et al (12) found no significant difference in IL-1ß –511 polymorphism between Japanese patients with COPD and control subjects, neither did Joos et al (44) between smoking subjects with fast or normal lung function decline. However, Joos et al (44) did find a difference in the distribution of the ratio between IL-1 receptor agonist and IL-1ß (IL1RN/IL1ß) haplotypes, which suggests that an imbalance in IL-1ß and its receptor agonist may increase the risk of COPD. Hegab et al (43) found that IL-1ß –511 tended to be different between patients with COPD (not stratified for cachexia) and HCs in an Egyptian population. This finding and the percentages of genotype distribution of IL-1ß –511 found by Hegab et al (43) are in accordance with our study. Hegab et al (43) also found that the distributions of the haplotype (IL-1ß –31 T/C: IL-1ß +3954 C/T) were different between patients with COPD and control subjects (43). The functional significance of these differences, however, is not clear. Locally, IL-1ß plays a role in the chemotaxis of neutrophils into the lungs, inducing the release of neutrophil elastase (45). IL-1ß furthermore induces proliferation of fibroblasts and synthesis of fibronectin and collagen (46). Systemically, IL-1ß has been shown to play a role in cachexia through suppression of food intake by stimulating release of catecholamines and through influencing macronutrient metabolism [reviewed in Yeh and Schuster (47)]. Unfortunately, we could not detect IL-1ß in this study. Looking at the available literature, no consensus has yet been reached on which allele is linked with a raised inflammatory status, which is partly because this gene is in linkage equilibrium with genes encoding for IL-1 and IL-1 receptor antagonist (48–50). These findings need to be confirmed in larger populations, and the possible consequences need to be studied.
In summary, in patients with COPD, who are characterized by an increased systemic inflammatory response, cachexia was not discriminatory for the amount of inflammation. This may be because the NCPs also had an impaired body-composition profile compared with HCs. Remarkably, CPs had a significantly different genotype distribution of IL-1ß –511 polymorphism than did HCs, which requires further investigation.
ACKNOWLEDGMENTS
RB performed the study with help from ECC. RB analyzed the data and wrote the manuscript with AMS. RFG and WMH performed the genotype analyses and provided the RBMD control group. DJS was responsible for the analysis of PSU. AMS and EFW provided the means to perform the study. All authors read, commented on, and contributed to the submitted manuscript. EFW serves as a consultant to GlaxoSmithKline (GSK) and is a member of the scientific advisory boards for GSK and Numico; he received lecture fees and research grants between 2001 and 2004 from GSK and Numico. None of the other authors had any conflict of interest to disclose.
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