• Metabolism and Body Composition in Chronic Inflammatory Arthritis: Prevention and Intervention through Pharmaceutical and Physical Means

      Metsios, Giorgos S. (University of Wolverhampton, 2007-12)
      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.
    • Metabolism in Patients with Rheumatoid Arthritis: Resting Energy Expenditure, Physical Activity and Diet-Induced Thermogenesis. Invited Review.

      Metsios, Giorgos S.; Stavropoulos-Kalinoglou, Antonios; Panoulas, Vasileios F.; Koutedakis, Yiannis; Kitas, George D. (Bentham Science Publishers, 2008)
      Metabolism is one of the most important physiological functions. Resting energy expenditure, physical activity and diet are the main factors of total metabolism but the contribution of these components to total energy expenditure may be significantly changed with chronic inflammatory diseases such as rheumatoid arthritis (RA). RA is a disease that alters normal metabolism due to the overproduction of pro-inflammatory cytokines and may lead to rheumatoid cachexia. This review focuses on the individual components of total energy expenditure and discusses how physical activity and diet may influence resting metabolism both in the healthy population as well as patients with RA. Moreover, information is provided regarding the available patents (i.e. equipment and prediction equations) that may be used in order to predict metabolism in the normal population and RA patients.
    • Resting metabolic rate in obese and nonobese Chinese Singaporean boys aged 13–15 y1–3

      Stensel, David J.; Lin, Fu-Po; Nevill, Alan M. (American Society for Nutrition, 2001)
      Background: Previous studies investigating the hypothesis that a low resting metabolic rate (RMR) is a cause of obesity yielded discrepant findings. Two explanations for these findings are the use of imprecise methods to determine obesity and a failure to control for differences in fat mass (FM) and fat-free mass (FFM) when comparing RMR values. Objective: This study tested the hypothesis that RMR is lower in obese than in nonobese boys (with the use of precise methods to quantify body fatness and with adjustment for differences in both FM and FFM). Design: Forty Chinese Singaporean boys aged 12.8–15.1 y were recruited. Boys were classified as obese (n = 20) or nonobese (n = 20) on the basis of their adiposity index (ratio of FM to FFM: >0.60 = obese, <0.40 = nonobese) determined by dualenergy X-ray absorptiometry. RMR was determined by using indirect calorimetry. RMR values were compared by using both linear (analysis of covariance) and log-linear (analysis of covariance with log-transformed data) regression to control for differences in FM and FFM. Results: Age, height, and FFM did not differ significantly between groups. Body mass was 13 kg greater and FM was 16 kg greater in the obese boys than in the nonobese boys (P < 0.001). After control for FFM and FM, RMR did not differ significantly between the groups. Conclusion: When body composition is appropriately controlled for, RMR does not differ significantly between obese and nonobese boys.
    • Resting metabolic rate in obese and nonobese Chinese Singaporean boys aged 13–15 y

      Stensel, David J.; Lin, Fu-Po; Nevill, Alan M. (American Society for Clinical Nutrition, 2001)
      Background: Previous studies investigating the hypothesis that a low resting metabolic rate (RMR) is a cause of obesity yielded discrepant findings. Two explanations for these findings are the use of imprecise methods to determine obesity and a failure to control for differences in fat mass (FM) and fat-free mass (FFM) when comparing RMR values. Objective: This study tested the hypothesis that RMR is lower in obese than in nonobese boys (with the use of precise methods to quantify body fatness and with adjustment for differences in both FM and FFM). Design: Forty Chinese Singaporean boys aged 12.8–15.1 y were recruited. Boys were classified as obese (n = 20) or nonobese (n = 20) on the basis of their adiposity index (ratio of FM to FFM: >0.60 = obese, <0.40 = nonobese) determined by dualenergy X-ray absorptiometry. RMR was determined by using indirect calorimetry. RMR values were compared by using both linear (analysis of covariance) and log-linear (analysis of covariance with log-transformed data) regression to control for differences in FM and FFM. Results: Age, height, and FFM did not differ significantly between groups. Body mass was 13 kg greater and FM was 16 kg greater in the obese boys than in the nonobese boys (P < 0.001). After control for FFM and FM, RMR did not differ significantly between the groups. Conclusion: When body composition is appropriately controlled for, RMR does not differ significantly between obese and nonobese boys.
    • Rheumatoid cachexia and cardiovascular disease

      Metsios, Giorgos S.; Stavropoulos-Kalinoglou, Antonios; Panoulas, Vasileios F.; Sandoo, A.; Toms, T. E.; Nevill, Alan M.; Koutedakis, Yiannis; Kitas, George D. (Clinical and Experimental Rheumatology Sas, 2009)
      Objective. It has been frequently stated that rheumatoid cachexia (RC) associates with increased cardiovascular risk; however, no studies to date have investigated this. The aim of this study was to investigate the association of RC with multiple novel and classical cardiovascular disease (CVD) risk factors and the presence of established CVD in rheumatoid arthritis (RA). Methods. A total of 34 RA patients with RC (RC+RA) were identified from a database of 400 RA patients using published RC criteria and compared to the remaining patients (RA-RC) who did not fulfil RC criteria. All patients were assessed for fat and fat-free mass, albumin (indicator of catabolism), disease activity/severity, novel and classical risk CVD factors and established CVD. Results. Fat-free mass (kg) and albumin (g/L) were significantly decreased in RC+RA vs. RA-RC patients: 37.3(33.9–41.6) vs. 45.9(41.2–55.5), p<0.001 and 39.6±6.7 vs. 42.4±4.9, p=0.001). Percent body fat was not significantly different. No significant differences were detected in either the classical or novel CVD risk factors, 10-year CVD risk or the prevalence of established CVD. Conclusions. RC does not appear to be associated with worse CVD profile in RA patients, but this needs to be confirmed in prospective studies.