Metabolism and body composition in chronic inflammatory arthritis : prevention and intervention through pharmaceutical and physical means

摘要

Background: Rheumatoid arthritis (RA) is characterised by excessive production of tumour necrosis factor alpha (TNFα). This leads to rheumatoid cachexia, a condition characterised by increased resting energy expenditure (REE) and loss of fat-free mass (FFM) leading to functional disability, decreased strength and balance. The aims of this research work was to: a) to develop a new REE equation in order to continuously monitor abnormal changes in REE in the RA population, b) to investigate if smoking further enhances hypermetabolism and c) to examine if the new anti-TNFα medication reverses this metabolic abnormality. Methods: 68 patients with RA were assessed for demographic and anthropometrical characteristics, REE (indirect calorimetry), body composition (bioelectrical impedance), and disease activity [C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), disease activity score 28 (DAS28) and health assessment questionnaire (HAQ)]. 20 of the total 68 patients, about to start anti-TNFα therapy, underwent the exact same aforementioned procedures but on three separate occasions (Baseline: two weeks prior to anti-TNFα treatment, Time-1 and Time-2: two weeks and three months, respectively, after the drug had been introduced. Results: Study 1: Based on FFM and CRP, a new equation was developed which had a prediction power of R2=0.76. The new equation revealed an almost identical mean with measured REE (1645.2±315.2 and 1645.5±363.1 kcal/day, p>0.05), and a correlation coefficient of r=0.87 (p=0.001). Study 2: Smokers with RA demonstrated significantly higher REE (1513.9±263.3 vs. 1718.1±209.2 kcal/day; p=0.000) and worse HAQ (1.0±0.8 vs. 1.7±0.8; p=0.01) compared to age and FFM matched RA non-smokers. The REE difference was significantly predicted by the interaction smoking/gender (p=0.04). Study 3: Significant increases were observed in REE (p=0.002), physical activity (p=0.001) and protein intake (p=0.001) between the three times of assessment. Moreover, disease activity significantly reduced [ESR (p=0.002), DAS28 (p=0.000), HAQ (p=0.000) and TNFα (p=0.024)] while FFM and total body fat did not change (both at p>0.05). Physical activity and protein intake were found to be significant within-subject factors for the observed REE elevation after 12-weeks on anti-TNFα treatment (p=0.001 and p=0.024, respectively). Conclusions: Findings from the first study revealed that the newly developed REE equation provides an accurate prediction of REE in RA patients. Moreover, the results from the second study showed that cigarette smoking further increases REE in patients with RA and has a negative impact on patients’ self-reported functional status. Finally, our data from the third study suggest that REE remains elevated not because of the maintenance of the RA-related hypermetabolism but due to the concomitant significant increases in physical activity and protein intake.