ETHNIC DIFFERENCES IN MARKERS OF INFLAMMATION WITH WEIGHT LOSS TANYA C. HYATT
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1 ETHNIC DIFFERENCES IN MARKERS OF INFLAMMATION WITH WEIGHT LOSS by TANYA C. HYATT BARBARA A. GOWER, COMMITTEE CHAIR MARCAS M. BAMMAN DOUGLAS C. HEIMBURGER GARY R. HUNTER BRADLEY R. NEWCOMER ROBERT A. OSTER A DISSERTATION Submitted to the graduate faculty of The University of Alabama at Birmingham, in partial fulfillment of the requirements for the degree of Doctor of Philosophy BIRMINGHAM, ALABAMA 2007
2 ETHNIC DIFFERENCES IN MARKERS OF INFLAMMATION WITH WEIGHT LOSS TANYA C. HYATT DEPARTMENT OF NUTRITION SCIENCES ABSTRACT Chronic diseases such as type 2 Diabetes Mellitis (T2DM) and cardiovascular disease (CVD) are accompanied by chronic low-grade systemic inflammation and are related to obesity and ethnicity. For instance, African-Americans (AA) have increased risk for developing T2DM and are more likely to be overweight relative to Caucasians (C). However, C have more intra-abdominal adipose tissue (IAAT) and have higher risk for CVD than AA. The influence that ethnicity has on disease risk is obscured by ethnic differences in fat distribution and sensitivity to insulin. Ethnic differences in markers of inflammation (MOI) have not been investigated. It is also unclear if the decreases in MOI seen with weight loss are mediated by fat mass losses in different fat depots, which may differ among the ethnicities. The current study aimed to determine if, independent of fat distribution, there are ethnic differences in MOI. Furthermore, this study was designed to determine the effect of weight loss, with and without exercise interventions, on MOI in AA and C women. 213 overweight, but otherwise healthy women were recruited for a weight loss protocol, with or without exercise. Subjects were randomized into intervention groups: diet only, diet + aerobic training, or diet + resistance training. Body fat distribution was determined ii
3 by dual-energy x-ray absorptiometry and computed tomography; insulin sensitivity by frequently sampled intravenous glucose tolerance test; and MOI by ELISA. The hypotheses of this study were that C women would have higher MOI than AA. However, after adjusting for IAAT, there would be no ethnic difference in MOI. Furthermore, independent of weight loss modality, MOI would be lower after weight loss and would specifically reflect the amount of fat lost. At baseline, plasma concentrations of TNF-α and its receptors were higher in C than AA. However, after adjusting for IAAT, the ethnic difference in TNF-α was attenuated to borderline significance (P=0.054). Among all women combined, all MOI decreased significantly with weight loss. When comparisons were conducted by ethnicity, all MOI decreased with weight loss among C, but only CRP decreased in AA. Overall, weight loss yielded favorable improvements in inflammation regardless of weight loss mechanism. iii
4 ACKNOWLEDGMENTS This has been the most enlightening, arduous, exhilarating, and tempestuous road of my life, all at once. I could never have imagined what this experience would do for me, from learning to understand what it takes to keep my passion alive to learning how to dive in and explore new opportunities. I am truly humbled by this experience. First, I should acknowledge my family and friends for enduring this long road with me; it hasn t been an easy one for any of us. You have all helped in such different and meaningful ways, I thank each of you for all that you do. I am extremely thankful to everyone who offered assistance throughout my tenure at UAB. Paul and David, you have both helped with so many details, I can t even begin to list them. All I can offer is a thank you, and maybe lunch. Radhika, a classmate, roommate, and true friend, you have helped me get this thing done. If it weren t for us pushing each other, and still I m not sure who was driving this runaway train, we might still be here running ELISA kits and digging through the freezer looking for samples. Alas, our hands can thaw and our minds can relax for a moment. Thank you so much for all that you have done. I must also acknowledge all of the people who have truly helped me attain this goal. Dr. Heimburger s generous assistance, through the Cancer Prevention and Control Training Program, provided me with a tremendous opportunity to work on my degree. I iv
5 thank him for his insight and direction. My committee has been truly supportive, offering words of encouragement and brilliant insight; I thank each of them for their guidance. Finally, I have to acknowledge the amazing mentorship I have gotten along the way. My primary advisor, Dr. Gower, has been a tremendous force since she stepped in as chair of my Ph.D. Committee. Her kind words of wisdom and encouragement, along with her calm inspiration, have pushed me to become a more thoughtful and efficient scientist. Her vast knowledge, not only in her own area of expertise, but in so many areas, has given me great insight into this project and opened my mind to so many more. Thank you, Dr. Gower, for your direction and support. v
6 TABLE OF CONTENTS Page ABSTRACT... ii ACKNOWLEDGMENTS... iv LIST OF TABLES... viii LIST OF FIGURES... ix LIST OF ABBREVIATIONS...x INTRODUCTION AND REVIEW OF LITERATURE...1 Overview...1 Markers of Inflammation...2 Obesity and Fat Distribution...5 Insulin Sensitivity and Disease Risk...7 Ethnic Differences...8 MOI and Weight loss...9 MOI and Exercise...12 Specific Aims...16 RESEARCH DESIGN AND METHODS...17 Subjects...17 Description of Tests...19 Body composition and fat distribution...19 Insulin sensitivity...20 Estimation of plasma MOI...21 Sample Size Considerations...21 Statistical Analysis...24 RESULTS...26 DISCUSSION...37 LIST OF REFERENCES...51 vi
7 APPENDIX: INSTITIUTIONAL REVIEW BOARD FOR HUMAN USE APPROVAL FORMS...60 vii
8 LIST OF TABLES Table Page 1 Descriptive statistics by ethnicity at baseline Pearson product moment correlations for markers of inflammation with total and regional adipose depots at baseline: All women combined, and by ethnicity Body composition, insulin sensitivity, and markers of inflammation with weight loss by ethnicity Body composition, insulin sensitivity, and markers of inflammation with weight loss by intervention group Comparisons of TNF-α with weight loss by ethnicity Comparisons of TNF-RI with weight loss by ethnicity Comparisons of TNF-RII with weight loss by ethnicity Comparisons of IL-6 with weight loss Comparisons of CRP with weight loss Pearson product moment correlations for markers of inflammation with insulin sensitivity at baseline. All women combined, and by ethnicity Predictors of insulin sensitivity among all women combined at baseline...36 viii
9 LIST OF FIGURES Figure Page 1 The TNF system decreased with weight loss in C but not AA. All elements of the TNF system were greater in C vs. AA...27 ix
10 LIST OF ABBREVIATIONS AA BMI C CAD CRP CT CVD DAG DSAAT DXA ELISA FSIGT GCRC HOMA IAAT IL-6 IRS-1 MCP MOI SAAT African-American body mass index Caucasian coronary artery disease C-reactive protein computed tomography cardiovascular disease diacylglycerol deep subcutaneous abdominal adipose tissue dual-energy X-ray absorptiometry enzyme-linked immunosorbent assay frequently sampled intravenous glucose tolerance test General Clinical Research Center homeostasis model assessment intra-abdominal adipose tissue interleukin-6 insulin receptor substrate-1 monocyte chemoattractant protein markers of inflammation subcutaneous abdominal adipose tissue x
11 SAT S I SSAAT TAAT TNF-α TNF-RI TNF-RII TSAAT T2DM UAB VLCD subcutaneous adipose tissue insulin sensitivity superficial subcutaneous abdominal adipose tissue total abdominal adipose tissue tumor necrosis factor α tumor necrosis factor receptor I tumor necrosis factor receptor II total subcutaneous abdominal adipose tissue type 2 diabetes mellitus University of Alabama at Birmingham very low calorie diet xi
12 1 INTRODUCTION AND REVIEW OF LITERATURE Overview Chronic diseases such as type 2 Diabetes Mellitus (T2DM), the metabolic syndrome, and cardiovascular disease (CVD) are accompanied by chronic low-grade systemic inflammation and are related to obesity and ethnicity. African-Americans (AA) have an increased risk of developing T2DM and are more likely to be overweight relative to Caucasians (C). However, C have more intra-abdominal adipose tissue (IAAT) and have higher risk for CVD than AA. Obesity increases risk for developing insulin resistance, as well as chronic disease, and both are associated with higher circulating markers of inflammation (MOI). However, the influence that ethnicity has on disease risk is obscured by ethnic differences in fat distribution and sensitivity to insulin. Ethnic differences in MOI have not been reported, with the exception of C-reactive protein (CRP), which was reported to be higher in AA (65). It is also unclear if the decreases in MOI seen with weight loss are mediated by fat mass losses in different fat depots, which also differ among the ethnicities. The current study aimed to determine if, independent of fat distribution, there are ethnic differences in MOI. Furthermore, this study aimed to determine the effects of weight loss, with and without exercise interventions, on MOI in AA and C women.
13 2 Markers of Inflammation Accumulating research suggests inflammation as a mechanism associating obesity and chronic metabolic disease. Adipose tissue has been found to express and secrete TNF-α, its receptors, TNF receptor I (TNF-RI) and TNF receptor II (TNF-RII), and interleukin-6 (IL-6). It has also been demonstrated that growing adipocytes recruit macrophages by releasing monocyte chemoattractant proteins (MCP). Specifically, human adipose tissue expresses C-C motif chemokine ligand-2 which is more commonly referred to as MCP-1. MCP-1 is increased in proportion to adiposity (13, 99). In fact, several studies have implicated MCP-1 and its receptor in the regulation of adipocyte function. In a mouse model of diet-induced obesity, MCP-1 receptor deficiency attenuated the development of obesity, adipose tissue macrophage accumulation, adipose tissue inflammation, and systemic insulin resistance (110). The number of macrophages present in adipose tissue is directly correlated with adiposity and adipose cell size in humans and in mice. Furthermore, there are no significant differences in number of macrophages in adipose tissue between the subcutaneous and IAAT depots in mice (22, 111, 115). The recruitment of large numbers of macrophages is likely to lead to a considerable amplification of pro-inflammatory factors, such as TNF-α and IL-6. These pro-inflammatory factors may lead to a disruption in normal metabolic processes, and eventually culminate in irregularities like insulin resistance. In fact, it is this initiation of the pro-inflammatory pathway that precedes disease, including CVD, the metabolic syndrome, and T2DM. TNF-α is a pro-inflammatory cytokine produced in adipose tissue, macrophages, and muscle. TNF-α has a pleiotropic effect on adipose tissue, including the stimulation
14 3 of lipolysis, apoptosis, and the regulation of cytokine expression (89, 95). The origin of TNF-α in chronic low-grade systemic inflammation is predominantly adipose tissue (20, 21). TNF-α is primarily produced by macrophages in adipose tissue, as opposed to adipocytes (111). TNF-α signaling is mediated by the transmembrane receptors, TNF-RI and TNF-RII. These receptors are active both as membrane integrated and soluble forms. For instance, TNF-RI can be directly expressed as a soluble isoform without the transmembrane domain (56). Furthermore, TNF-RII is released from the membrane via proteolytic cleavage. In addition to mediating TNF-α signaling, both TNF receptors are the naturally occurring inhibitors of TNF-α (24). Accumulating data point to an effect of TNF-α on insulin signaling, perhaps via serine phosphorylation of insulin receptor substrate-1 (IRS-1) in skeletal muscle (49, 51). This may inhibit the ability of insulin to stimulate glucose transporter-4 translocation to the cell membrane, thereby reducing glucose uptake (48, 49, 53). TNF-α impairs insulin-stimulated rates of glucose storage in cultured human muscle cells (42). Also, obese mice with a knockout of the TNF-α gene are protected from insulin resistance (104). It has been proposed that TNF-α causes insulin resistance in vivo indirectly by increasing the release of free fatty acids from adipose tissue (11, 38, 98). However, Bruce and colleagues demonstrated that TNF-α had no effect on muscle fatty acid oxidation but increased fatty acid incorporation into diacylglycerol (DAG), which may be involved in the development of TNF-induced insulin resistance in skeletal muscle (12). DAGs are known activators of conventional and novel protein kinase C isoforms that inhibit IRS-1. Although the mechanisms aren t entirely clear, TNF-α plays an important role in cellular glucose utilization and the development of insulin resistance and T2DM.
15 4 IL-6 is another cytokine produced in adipose tissue, as well as contracting skeletal muscle and other cell types. It is estimated that as much as 50% of total circulating concentrations of IL-6 originates from adipose tissue in healthy subjects (111). In addition, in adipose tissue, IL-6 is produced by macrophages as well as adipocytes, to a lesser degree (111). The role of IL-6 with regard to the inflammatory cascade is relatively unclear, with some reports suggesting primarily anti-inflammatory effects and others alleging pro-inflammatory action. Increased IL-6 has been reported in obese individuals and in type 2 diabetics (107). An increase in IL-6 is thought to precede and stimulate the liver s production of CRP, which is known to be a sensitive marker of inflammation. The association between IL-6 and CRP has been interpreted to indicate a pro-inflammatory role for IL-6. However, when human recombinant IL-6 was given to diabetic patients, plasma insulin concentrations decreased to levels comparable with age and BMI-matched controls. These findings might indicate that IL-6 enhances insulin sensitivity (S I ) (86). Mice, pretreated with IL-6, had blunted skeletal muscle glucose disposal and increased intramuscular fatty acyl CoA (62). Intramuscular fatty acyl CoAs are increased with obesity (55), are inversely related to S I (19), and decrease with weight loss (54). The effect of IL-6 on insulin action and lipid accumulation was similar to that of lipid infusion alone, indicating that the effect of IL-6 on muscle metabolism may be mediated through increased fat availability. The local inflammatory cascade that produces TNF-α and IL-6 is accompanied by a systemic response known as the acute-phase response. This includes the production of several hepatocyte-derived acute phase proteins, including CRP. Cytokines, in particular IL-6, are the main inducers of the acute phase response; in fact, this can be reproduced
16 5 with the injection of TNF-α and IL-6 (2, 3, 24-26). This is not surprising, as CRP has an IL-6 response element in the promoter region of its gene, indicating that IL-6 may facilitate the production of CRP. A very tight correlation of IL-6 and CRP exists, although this relationship does not exist with other cytokines (73). Like many mediators of inflammation, CRP has pleiotropic effects. Pro-inflammatory actions include upregulating the expression of adhesion molecules in endothelial cells, and increasing the release of IL-6 and TNF-α (7, 106). Anti-inflammatory effects include modulation of the complement pathway, the host defense mechanisms in the inflammatory response. When CRP is present, there is activation of the early complement proteins, but very little activation of the late complement proteins, which elicit a very strong inflammatory response (77). In this way, CRP can participate in host defense systems while limiting the potentially damaging inflammatory effect of the late stage complement components. This has been further demonstrated in humans. There is a polymorphism in the human CRP gene that results in lower CRP production. Furthermore, this reduced CRP production in these individuals is associated with elevated risk of developing lupus, which is an auto-immune disease resulting from hyperactive lymphocytes (93). Obesity and Fat Distribution The current view of adipose tissue is that of a secretory organ. As such, adipose tissue generates and responds to signals that modulate appetite, energy expenditure, S I, and inflammation. The basis for the latter is that circulating concentrations of CRP, TNF-α and its receptors, and IL-6 are increased in the obese (30, 114, 117). Many studies, although not all, have shown that IAAT was better associated with S I than
17 6 subcutaneous adipose tissue (SAT). This produced the idea that IAAT may be better associated with circulating MOI. IAAT may also be the depot of concern with regard to MOI because of its proximity to the portal venous system, enabling products of IAAT to be delivered directly to the liver. These IAAT-derived products amplify the inflammatory signal by increasing production of CRP and other inflammatory mediators. IL-6 is thought to be derived predominantly from IAAT. In in vitro assays, IAAT released approximately 2-3 times more IL-6 than subcutaneous fat (28, 33). In fact, IL-6 and CRP are directly correlated with intra-abdominal obesity, and CRP is significantly and positively correlated with body mass index (BMI) and waist circumference (43, 88). It appears that obesity is associated with elevated adipose tissue mrna expression of TNF-α (predominantly from macrophages in adipose tissue). This elevation is positively associated with hyperinsulinemia (50, 52, 60, 114). Winkler and collaborators found that in overweight subjects, TNF-α expression in SAT and IAAT correlated with serum TNF-α concentrations, and that serum TNF-α and TNF-RII were elevated in overweight compared to lean (114). In a study examining obese Korean subjects, who have even greater IAAT than C, there were no significant correlations between TNF-α and any measure of adiposity (83). However, in these individuals, IL-6 and CRP were significantly correlated with IAAT and BMI, respectively. These findings are in agreement with Festa, et al, who found that even after adjusting for S I, CRP concentrations correlated with measures of body fat from bioelectrical impedance and waist/hip circumferences (29). Giugliano and colleagues performed large volume liposuction of SAT on 30 healthy obese women and found not only a significant improvement in S I, but a significant reduction in serum IL-6 and TNF-α (36). This
18 7 implies that a significant amount of circulating MOI could be produced in the subcutaneous abdominal adipose tissue (SAAT) depot. Klein et al found no effect of subcutaneous abdominal liposuction on insulin action, or on circulating concentrations of TNF-α, IL-6 or CRP (64). This suggests that these MOI may be produced primarily in the IAAT depot. Questions still exist over the associations between MOI and various abdominal fat depots, including IAAT, superficial, and deep subcutaneous abdominal adipose tissue (SSAAT and DSAAT, respectively). Additionally, the conflicting results generated by these liposuction studies highlight the need for further examination of the relationship between fat distribution and circulating MOI. Insulin Sensitivity and Disease Risk Numerous studies have shown an association between MOI and S I regardless of the level of adiposity (29, 74, 100). Because both inflammation and insulin resistance precede T2DM, understanding the relationship between the two is imperative. Hanley, et al showed that increased MOI have a role in decreasing S I, that CRP was significantly correlated with S I, obesity measures, glucose and lipids, and that CRP was associated with the metabolic syndrome and abdominal obesity (43). Esposito, et al found that among obese premenopausal women, IL-6 explained 15% of the variance in insulin sensitivity as determined by homeostasis model assessment (HOMA) (27). In normalweight, healthy subjects, insulin sensitivity (via clamp) was inversely associated with IL- 6, and oxidative glucose disposal was inversely associated with CRP (47). Also, patients with T2DM demonstrate high expression of TNF-α in skeletal muscle and plasma (96). Furthermore, elevated CRP and IL-6 predict the development of T2DM in middle-aged
19 8 women (88). These studies clearly support the existence of a relationship between MOI and S I and underline the need for a better understanding of the relationship between them. Therapeutically, inhibition of TNF-α in obese diabetics had no effect on S I (80). Although this only suggested that alleviating elevated TNF-α did not change S I, the study did not aim to demonstrate a causal relationship. Coculture of human skeletal muscle with adipocytes impaired insulin signaling, but the effect was independent of TNF-α (23). In addition, incubating human skeletal muscle with TNF-α did not impair insulinmediated glucose uptake (79). It must be noted in these studies that in vivo, TNF-α is not present alone. Therefore it should not be assumed that TNF-α alone should change S I. Even when TNF-α is inhibited in vivo, persistent obesity will contribute to elevations in other MOI, which could prevent significant improvements in S I. Therefore, it may be that the alleviation of obesity, through the reduction in all MOI, is necessary to improve tissue sensitivity to insulin. Ethnic Differences Ethnic differences in fat distribution and S I have been clearly described. Consequently, the possibility that there are ethnic differences in MOI exists. AA are at a disproportionate risk for obesity (81) and T2DM (44), yet C have more IAAT (5, 69) and C diabetics have higher risk for CVD, namely atherosclerosis, than AA (32). Increased accumulation of IAAT increases insulin resistance and risk for developing T2DM, as well as CVD. However, AA, with less IAAT than C, are significantly more insulin resistant. Previous studies have indicated that healthy, non-diabetic AA have lower S I relative to C and these ethnic differences have been demonstrated in both adults and
20 9 children (6, 37, 40). However, few studies have examined differences in circulating concentrations of MOI between racial groups. One such study examined the differences in inflammatory and metabolic markers between Afro-Caribbeans and C. That study found elevated TNF-α and IL-6 in the Afro-Caribbean population (58). In contrast, Heald, et al showed reduced CRP in Afro-Caribbeans (45). In a large population-based study, AA women had higher CRP levels compared to C (31). This trend was seen even after data were adjusted for cardiovascular risk factors, education status, and lifestyle factors (31). Unfortunately, no adjustment was made for adiposity in this study. Also, data from the Women s Health Study showed that AA had higher levels of CRP, relative to C, even after adjusting for similar covariates (4). Because there were no measures of fat distribution in these studies, it is not clear whether ethnic differences in fat distribution influenced the differences seen in MOI. The present study aimed to examine the differences in MOI between ethnicities, with adjustment for fat distribution. MOI and Weight loss Because MOI are associated with obesity and metabolic disease risk, weight loss and its effects on MOI have been examined in several studies. Several MOI, including CRP, IL-6, TNF-α, and its receptors are reduced after weight loss achieved through shortterm caloric restriction (8, 9, 46) and long term life-style modifications including reduced energy intake and increased physical activity (72, 101, 118). Diet-induced weight loss, by very low-calorie diet (VLCD) for 3 weeks, resulted in a decrease in IL-6, but not CRP or TNF-α in obese C women (8). A major confounder to the protocol executed in that study was that the post-weight loss measurements were collected while the subjects were
21 10 still in negative energy balance, as opposed to while the subjects were on a weightmaintenance diet. In another study by the same author, TNF-RI, but not TNF-RII, decreased significantly with the same weight loss protocol (9). This supports the finding in earlier studies that human adipose tissue produces TNF-RI, but not TNF-RII (76). Interestingly, the degree of change in fat mass by dual-energy X-ray absorptiometry (DXA) was inversely associated with the degree of change in TNF-RI. These results support earlier findings that IL-6 stimulates the production of TNF-RI which inhibits the production of TNF-α (24). In addition to cellular signaling, there are at least two potential roles for TNF receptors in the inflammatory process: 1) TNF receptors may act as a binding protein, thereby increasing the half-life of TNF-α, and acting as a proinflammatory factor and, 2) TNF receptors may act to inhibit the production of TNF-α thereby act as an anti-inflammatory factor. The anti-inflammatory nature of TNF receptors may result in higher concentrations of these receptors after weight loss instead of the predicted decrease seen with other MOI. These particular studies show the changes in concentrations of MOI with negative energy balance, as well as weight loss. Studies are needed maintaining energy balance after weight loss to help further elucidate the effect of weight loss on circulating concentrations of MOI. Another study in 37 women (30 C and 7 AA) showed that increases in glucose utilization and S I with weight loss were related to reductions in circulating cytokines, TNF-RI and IL-6, independent of decreases in total body fat and IAAT (94). In that study, all subjects were weight stabilized for 2 weeks prior to all testing, and a eucaloric diet was provided for the 2 days immediately before. However, these subjects never obtained a normal body weight and all women remained overweight or obese after the
22 11 intervention (mean BMI was 37.1 ± 1.4 after weight loss). In another study conducted by Esposito et al, a reduction in body weight by >10% resulted in significant decreases in glucose, insulin, IL-6 and CRP. However, no weight-maintenance period was established and no body composition measures were evaluated in their study (27). Esposito et al. also found that BMI and HOMA were independently and significantly associated with IL-6, and that in the intervention group, the reduction in IL-6 was related to the reduction in BMI (r=0.35, P=0.02). These studies highlight the need for a well-controlled dietary intervention, with a weight-stabilized data-collection period, so that the effect of weight loss on MOI can be examined. One postulated mechanism for weight loss induced reduction in MOI is through a decrease in adipose tissue cytokine production. A few studies have examined the effects of weight loss on cytokine gene and protein expression in SAT and found decreased production of IL-6 and TNF-α locally. More recently, gene-expression profiling showed that pro-inflammatory genes were down-regulated and anti-inflammatory genes were upregulated in SAT after 28 days on a VLCD (16). In a study involving obese women, 3 weeks on a VLCD (with only 5% reduction in BMI) reduced circulating IL-6 by 15% (8). Furthermore, weight loss through caloric restriction reduced TNF-α gene and protein expression (61) as well as its release from abdominal adipose tissue (14). Most of the weight loss studies showed the magnitude of decrease in MOI to be linearly related to the amount of weight lost. In postmenopausal women on a 14 month weight reduction program, reductions in CRP concentrations correlated with changes in body weight and fat mass. Decreases in CRP, IL-6, and TNF-α in premenopausal women after 10% weight reduction correlated with changes in BMI, but were more strongly
23 12 related to changes in waist-hip ratio (72, 118). These studies suggest that IAAT may be strongly associated with these MOI, and may be related to the reductions in MOI seen with weight loss. However, more work is needed to further examine this issue. Consequently, the present study will examine not only this relationship, but will do so among different ethnic groups, because of the ethnic differences in fat distribution and metabolic parameters. MOI and Exercise Because cytokines are produced in contracting skeletal muscle, many researchers have looked into the influence of exercise on MOI. Although TNF-α has traditionally been viewed as one of the primary inducers of acute phase reactions, the majority of studies have shown that the circulating concentration is either unchanged following exercise, or exhibits small, delayed increases (85). In contrast, serum IL-6 concentration increases exponentially with exercise and declines in the post-exercise period. Therefore, IL-6 and TNF receptors might have an anti-inflammatory role in exercise, and act to inhibit the release of TNF-α. This may explain the findings in some studies that TNF-α actually decreases with exercise. Toft et al found that in young and elderly subjects, IL-6 concentrations increased after eccentric exercise (102). They also found that it peaked at 4 hours, and returned to pre-exercise levels the day after exercise. They also found no change in plasma TNF-α. However, TNF receptors were increased after exercise, peaked at 1 and 2 hours post-exercise in the young and elderly, respectively, returned to baseline 3 hours after exercise in the elderly, but did not return to pre-exercise levels in young subjects until day 2.
24 13 Low-grade systemic increases in IL-6 represent a strong prognostic risk factor in T2DM and CVD. However, it seems a paradox that large amounts of IL-6 are released during acute bouts of exercise, which is considered to be health-beneficial. IL-6 is often postulated to cause insulin resistance. However, some studies have shown S I to be increased during and following exercise when IL-6 is elevated pronouncedly in circulation. IL-6 knock-out mice develop late-onset obesity and decreased glucose tolerance, which can be reversed by IL-6 administration (108). Conversely, transgenic mice expressing active I Kappa B kinase β in hepatocytes have low-level activation of nuclear factor-κβ. In addition, they have increased expression of IL-6 as well as insulin resistance (15). With regard to MOI, most studies thus far have examined either acute bouts of exercise or cross-sectional associations between MOI and physical activity. Although acute bouts of exercise are well known to increase concentrations of pro-inflammatory cytokines and acute-phase reactants, chronic physical activity may reduce basal concentrations of these MOI (85). Cross-sectional observation studies show an inverse association between MOI and physical activity (17). Some studies, including the Nurses Health Study II, showed an inverse, independent dose-response relationship between CRP concentrations and physical activity in women (1, 63, 87). In these studies, the relationship was independent of level of adiposity. However, some of the reports that contradict these findings may be confounded by small sample size (87, 90). Overall, data from observational studies showed that greater physical activity was associated with lower MOI. However, few studies have looked at long-term exercise interventions and the potential changes in circulating MOI. Those studies that did look at long-term
25 14 exercise interventions examined changes in circulating concentrations of MOI with exercise in conjunction with weight loss. As previously discussed, it has been widely demonstrated that weight loss decreases MOI. Therefore, the effect of the exercise component of these interventions was confounded by the weight loss. Until recently, there were no data from prospective randomized controlled trials to conclude that chronic exercise training reduces chronic inflammation. However, several uncontrolled studies of exercise showed an effect on specific MOI. For instance, patients exhibiting chronic heart failure showed reduced TNF-α concentrations following 12 weeks of aerobic training (67). In a similar cohort, 16 weeks of combined resistance and aerobic training decreased both TNF receptors but not TNF-α itself (18). In overweight women, aerobic exercise training for 5 months lowered concentrations of TNF-α and its receptors (103). Levels of CRP, but not IL-6 decreased significantly in 20 postmenopausal women who completed a 14-day diet and aerobic exercise intervention. However, the magnitude of decrease in CRP was not significantly related to the magnitude of weight loss (45% and 4%, respectively) (109). In another study examining resistance training in older patients, TNF-α mrna and protein levels decreased in skeletal muscle with the intervention (39). All of these studies had a small number of participants, were conducted in populations with elevated MOI that may or may not be related to body fat, and had relatively short durations. One study of 235 coronary artery disease (CAD) patients that incorporated a control group demonstrated that an exercise training program reduced CRP in patients with CAD, but did NOT affect CRP in 42 patients who did not exercise (75). These changes in CRP concentrations were not associated with changes in body weight or
26 15 percent body fat. This suggests that the exercise training effect may have been independent of body fat loss. Another group found an independent effect of exercise training in postmenopausal women who underwent 6 months of dietary weight loss with or without aerobic exercise training. The authors showed decreases in IL-6 and TNF-RI differed significantly between the groups with these changes in concentrations being inversely related to changes in aerobic fitness (116). Nicklas, et al conducted a randomized controlled clinical trial in 316 older, obese subjects with 4 treatment groups: healthy lifestyle control, dietary weight loss, exercise, and diet with exercise (78). Their study showed that a dietary weight loss intervention provided significantly greater reductions in concentrations of CRP, IL-6 and TNF-RI than did no weight loss treatment. Furthermore, exercise training did not have a significant effect on these MOI and there was no significant interaction between weight loss and exercise training. Also, their study tried to examine effects of ethnicity on these responses to the treatment regimens. Unfortunately, they did not have statistical power because the study group included men as well as women. In the present study, we will be able to test the effects of diet and exercise on younger women, as well as determine any ethnic differences in response to the interventions.
27 16 Specific Aims 1) To determine if there are ethnic differences in MOI and whether these differences are eliminated by adjusting for dissimilarities in fat distribution seen between ethnicities. Hypothesis: C women will have higher IAAT-associated MOI than AA women. After adjusting for IAAT, there will be no ethnic difference in MOI. 2) To determine if MOI reflect changes in fat distribution with weight loss. Hypothesis: MOI will be lower after weight loss. Change in MOI will be explained by the change in IAAT. C women will have a greater decrease in MOI than AA women. This decrease will be associated with a greater loss of IAAT in C women compared to AA women. 3) To identify independent effects of exercise and body composition on MOI with weight loss. Hypothesis: After weight reduction, exercise will be independently associated with a decrease in MOI. 4) To determine if circulating MOI are associated with S I, and whether this differs with ethnicity. Hypothesis: MOI will be inversely associated with S I in both ethnicities, after adjusting for body fat distribution.
28 17 RESEARCH DESIGN AND METHODS Subjects 213 healthy, overweight, premenopausal women were recruited for this study. Inclusion criteria: Overweight women (BMI kg/m 2 at baseline) Premenopausal, age % AA, 50% C Sedentary Normal glucose tolerance (determined by oral glucose tolerance test) Family history of overweight/obesity No use of medications that affect body composition or metabolism All women were nonsmokers and reported experiencing menses at regular intervals. Because metabolism may be affected by menstrual cycle, all testing was performed in the follicular phase of the menstrual cycle (within 10 days of menses). Before participating in the study, the women provided informed consent to the protocol, which was approved by the Institutional Review Board and Human Services Regulations for Protection of Human Research Subjects. Subjects were selected from participants in an ongoing study designed to examine metabolic factors that predispose women to weight gain. Subjects were evaluated in the overweight state and reassessed in the weight-reduced state. Initially, they were
29 18 maintained in weight stabilization for 4 weeks through dietary control. During this time their body weights were measured 3 5 times weekly at the General Clinical Research Center (GCRC) and at the end of the 4 weeks, they were admitted to the GCRC for a 4 day evaluation. A macronutrient-controlled diet was provided during the final 2 weeks of weight maintenance. The energy content was appropriately adjusted to ensure a stable body weight ( 1% variation from the subjects weight at the beginning of the 4 weeks). All diets consisted of approximately 22% of energy from fat, 23% from protein, and 55% from carbohydrate. Subjects were randomized to one of three intervention groups: diet only, diet + aerobic training, or diet + resistance training. After discharge from the initial GCRC inpatient visit, the GCRC kitchen provided all meals for the period of weight reduction. Subjects were provided a 3350 kj (800 kcal) diet, which was designed to meet all nutrient requirements excluding energy requirements. Stouffer s Lean Cuisine entrées (Nestlé Food Co, Solon, OH) were provided for lunch and dinner, and alcohol intake was not permitted during the study. Subjects were maintained on the diet until 10 kg in body weight was lost and a BMI < 25 was achieved. Having attained a normal body weight, subjects then repeated the 4-week protocol of energy balance followed by the 4-day admission and evaluation at the GCRC. Subjects assigned to the exercise groups participated in 3 supervised training sessions each week throughout the study. Sessions lasted approximately 50 minutes and took place in exercise rooms in the Bell Training Facility or in the exercise facility in the Nursing building on the University of Alabama at Birmingham (UAB) campus. Aerobic training included 3 sessions/week of walking, running, stair-stepping or cycle ergometry.
30 19 Exercise intensity increased each week to achieve 80% of subjects maximum heart rate for 40 minutes. Resistance training included 3 sessions/week of 2 sets of 8 exercises, with 10 repetitions/set, with intensity based on 80% of the maximum weight that can be lifted one time. Strength exercises included leg press, squats, leg extension, leg curl, elbow flexion, lateral pull-down, bench press, military press, lower back extension, and bent leg sit-ups. Subjects assigned to the exercise groups during weight loss continued in the same exercise groups during the weight maintenance phase. Subjects on the exercise interventions were tested an average of hours after the last exercise bout. Description of Tests Body composition and fat distribution. Total and regional body composition, including total fat mass, percent body fat, and lean body mass, were measured by DXA with a Lunar Prodigy densitometer (Lunar Radiation Corp, Madison, WI). The DXA machine was located in the Department of Nutrition Sciences at UAB, and used the body composition Adult Software Version 1.33 (GE-Lunar, Madison, WI). Subjects were scanned in light clothing while lying flat on their backs with arms at their sides. Total abdominal (TAAT), IAAT and SAAT, including total (TSAAT), SSAAT, and DSAAT, were analyzed by computed tomography scanning with a HiLight/Advantage Scanner (General Electric, Milwaukee) located in the UAB Department of Radiology. Subjects were scanned in the supine position with arms stretched above their heads. A 5mm scan at the level of the umbilicus (approximately the L4-L5 intervertebral space) was taken. Scans were analyzed for cross-sectional area (cm 2 ) of adipose tissue using the density contour program with Hounsfield units for
31 20 adipose tissue set at -190 to -30. All scans were analyzed by the same individual. The CV for repeat cross-section analysis of scans among 40 subjects in our laboratory is less than 2%. Insulin sensitivity. Whole body S I was assessed with an insulin-modified, frequently-sampled intravenous glucose tolerance test (FSIGT). Prior to testing, and after an overnight fast, flexible intravenous catheters were placed in the antecubital spaces of both arms. Three 2.0 ml blood samples were taken over a 20-min period for determination of basal glucose and insulin (the average of the values is used for basal "fasting" concentrations). At time "0", glucose (50% dextrose; 11.4 g/m 2 ) was administered intravenously. Insulin (0.02 U/kg, Humulin, Eli Lilly and Co., Indianapolis) was injected at 20 min post glucose injection. Blood samples (2.0 ml) were then collected at the following times (min) relative to glucose administration: 2, 3, 4, 5, 6, 8, 10, 12, 15, 19, 20, 21, 22, 24, 26, 28, 30, 35, 40, 45, 50, 55, 60, 70, 80, 100, 120, 140, 180, 210, 240, 300. Sera were stored at - 85 o C until analyzed. Glucose and insulin values were entered into the MINMOD computer program (Millenium ver., Richard N. Bergman) for determination of S I. Glucose was measured using an Ektachem DT II System (J&J Clinical Diagnostics). In our laboratory, this analysis had a mean intra-assay CV of 0.61%, and a mean inter-assay CV of 2.56%. Insulin was assayed in duplicate 100 µl aliquots using double-antibody radioimmunoassay (Linco Research Inc., St. Charles, MO). In our lab, this assay had a sensitivity of 3.35 µiu/ml, a mean intra-assay CV of 3.49%, and a mean inter-assay CV of 5.57%.
32 21 Estimation of plasma MOI. All MOI were assessed using enzyme-linked immunosorbent assays (ELISA). All samples were analyzed in duplicate. Likewise, all baseline and Weight-reduced samples were assayed on the same ELISA plate. TNF-α was analyzed using the high sensitivity ELISA kit (Quantikine HSTA00C, R&D Systems). Plasma concentrations of TNF-α were below the minimum detectable concentration for the TNF-α ELISA kit. Therefore, these samples were reanalyzed to verify the concentrations. TNF-RI was measured with the EASIA TM ELISA kit (KAC1761, Biosource, CA). Concentrations of TNF-RII were measured with the EASIA TM ELISA kit (KAC1771, Biosource, CA). IL-6 was assayed using the high-sensitivity ELISA kit (Quantikine HS600B, R&D Systems, Minneapolis, MN). Plasma CRP was assayed with the high sensitivity ELISA kit ( s, ALPCO, Windham, NH). Plasma CRP concentrations >10 mg/l represent an acute state of inflammation (84); therefore all values of CRP >10 mg/l were omitted from analyses. Sample Size Considerations The sample size for aims 1 and 4 was 213 women from the ongoing parent study entitled Exercise Training in Obesity Prone Black and White Women. Of these, 105 were C and 108 were AA. The sample size for aims 2 and 3 was 126 women from the previously mentioned parent study. Of these, 61 were C and 65 were AA. This sample size included those subjects who adhered to the diet and exercise requirements of the
33 22 parent study. In total, 83 subjects dropped out of the study during the intervention, and plasma samples were not available for 4 subjects. Because we wanted to investigate independent effects of weight loss and exercise on MOI, it was necessary to consider adherence to the exercise intervention. Our exercise training protocols required 3 exercise sessions per week, with 2 sessions per week required to achieve a training effect. Therefore, we also conducted all analyses in women who had >67% adherence to the exercise intervention protocol. Eliminating subjects with <67% adherence to the exercise intervention reduced our sample size to 102. However, excluding those subjects with <67% adherence to the exercise intervention protocol did not alter results. Therefore, all subjects were included in the final analyses. Likewise, because exercise induces an acute response in MOI, we adjusted all MOI for the time since the last exercise bout and found that it did not alter the results in our cohort. Also, within our dataset, many TNF-α values were below the minimum detectable concentration (0.50 pg/ml). In fact, there were 4 baseline samples that were below the minimum, 19 weight-reduced samples below the minimum, and 30 subjects had samples at both time points that were below 0.50 pg/ml. To avoid eliminating 53 of 126 subjects from analyses, these values were set equivalent to the minimum detectable concentration. As most of them were undetectable in the weight-reduced sample, or in both samples, we either saw a decrease with weight loss, or no change. For the purpose of performing power calculations for comparisons between AA and C (aim 1), we used results from our pilot data. The following calculations assumed group sizes of 108 (AA) and 105 (C), a two-sided two-group t-test, and a significance
34 23 level of 5%. Estimates of the common standard deviation obtained from our pilot data were 1.1 pg/ml for TNF-α, 1.5 pg/ml for IL-6, and 25.7 ng/ml for CRP. We had at least 80% power to detect mean ethnic group differences of 0.5 units in TNF-α, 0.6 units in IL- 6, and 10.0 units in CRP as being statistically significant. For the purpose of performing calculations for comparisons of the changes in outcomes of interest with weight loss (aim 2), we used estimates of the common standard deviation (of the change) obtained from our pilot data. The following calculations assumed an overall group size of 126, group sizes of 65 for AA and 61 for C, a two-sided paired t-test, and a significance level of 5%. Our current study had at least 80% power to detect an overall change of 0.3 pg/ml in TNF-α, 0.7 pg/ml in IL-6, and 6.0 ng/ml in CRP as being statistically significant. For AA, we had at least 80% power to detect changes of 0.4 pg/ml in TNF-α, 1.0 pg/ml in IL-6, and 8.4 ng/ml in CRP as being statistically significant. For C, we had at least 80% power to detect changes of 0.4 pg/ml in TNF-α, 1.0 pg/ml in IL-6, and 8.6 ng/ml in CRP as being statistically significant. To examine correlations between pairs of study variables (aims 2, 3, and 4), we had 80% power to detect statistically significant correlations of 0.25 and greater for the entire weight loss group (n=126), of 0.35 and greater for AA women (n=65) and 0.36 and greater for C women (n=61) involved in the weight loss protocol, and of 0.20 and greater for all women (n=213). These calculations assumed a significance level of 5%, a twosided statistical test on the correlation coefficient, and the approximate normality of the transformed correlation coefficient as implemented in the nquery Advisor software package.
35 24 With respect to multivariate relationships among study variables (aims 2, 3, and 4), our power calculations were based on a test of the squared multiple correlation (R 2 ) for a multiple linear regression model. In a 5-parameter model, we had 80% power to detect an R 2 (which is also the effect size) of for all women involved in the weight loss arm, of for AA women and for C women participating in the weight loss protocol, and of for all women. Finally, effect sizes of (for all weight loss data), (for AA women), (for C women), and (for intervention groups) were required to provide 80% power for a test of an individual parameter within a linear regression model for the respective groups of women. Statistical Analysis Descriptive statistics were computed for all study variables of interest. Distributions of these variables were examined. Continuous variables that were known to deviate from a normal distribution, such as serum analytes, were log transformed (using the log base 10 transformation) prior to statistical analysis. All statistical tests were twosided and were performed using a Type I error rate of All statistical analyses were performed using SAS (version 9.1; SAS Institute, Inc., Cary, NC). Overall comparisons between the two ethnic groups (aim 1) were performed using the two-group t-test. Overall comparisons of the change in fat and MOI with weight loss for all women, by ethnic group, and by intervention group were performed using repeated-measures 2-way ANOVA (aims 2 and 3). Repeated-measures mixed-models analyses were used to evaluate changes in MOI after weight loss. Independent variables included in these models were intervention group, ethnicity, time, indices fat mass and
36 25 IAAT. Our original hypotheses were that loss of fat and IAAT would determine decreases in MOI with weight loss, so these variables were used, although other fat depots were tested as well. Appropriate interaction terms, such as intervention group*time, ethnicity*time, intervention group*ethnicity, and intervention group*ethnicity*time were included. Pearson correlation coefficients were calculated to examine associations (aims 2, 3, and 4) between two continuous variables. These analyses were conducted among the entire cohort and by ethnicity due to possible ethnic differences in fat distribution and S I. Finally, multiple linear regression modeling was used to determine significant predictors of S I (aim 4). These regression models included regional adipose tissue and MOI as independent variables. Correlation and regression coefficients in all models were tested for statistical significance.
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