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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Obesity (Silver Spring). Author manuscript; available in PMC Jun 20, 2013.
Published in final edited form as:
PMCID: PMC3687549
NIHMSID: NIHMS343580
Markers of Inflammation and Fat Distribution following Weight Loss in African American and Caucasian Women
Gordon Fisher,1 Tanya C. Hyatt,1 Gary R. Hunter,2 Robert A. Oster,3 Renee A. Desmond,3 and Barbara A. Gower1
1Department of Nutrition Sciences, University of Alabama-Birmingham, Birmingham AL, USA.
2Department of Human Studies, University of Alabama-Birmingham, Birmingham AL, USA.
3Department of Medicine, University of Alabama-Birmingham, Birmingham AL, USA.
Corresponding author: Gordon Fisher, Ph.D., University of Alabama at Birmingham, Department of Nutrition Sciences, 413 Webb Building, 1675 University Blvd., Birmingham, AL 35294-3360, Phone: (205) 934-6177; Fax: (205) 934-7050; grdnfs/at/uab.edu
Changes in markers of inflammation (MOI) and fat distribution with weight loss between African American (AA) and Caucasian (C) women have yet to be characterized. The purpose of this study was to examine potential ethnic differences in MOI and regional fat distribution with weight loss, and identify the associations between these markers and changes in regional fat distribution with weight loss among AA and C women. Subjects were 126 healthy, premenopausal women, BMI 27–30 kg/m2. They were placed on a weight loss intervention consisting of diet and/or exercise until a BMI < 25 was achieved. Fat distribution was measured with computed tomography, and body composition with dual-energy X-ray absorptiometry. Serum concentrations of tumor necrosis factor (TNF)-α, soluble tumor necrosis factor receptor (sTNFR)-I, sTNFR-II, C-reactive protein (CRP), and interleukin (IL)-6 were assessed. All MOI and adiposity measures significantly decreased with weight loss. Significant ethnic differences with weight loss were observed for fat mass, body fat, intra-abdominal adipose tissue (IAAT), sTNF-RI, and sTNF-RII. Mixed-model analysis indicated that adjusting for change in IAAT explained ethnic differences in change in TNF-α and the decrease in TNF-α with weight loss, while total fat mass only explained the decrease in sTNF-RI and sTNF-RII with weight loss. In conclusion, all MOI decreased following weight loss among C, whereas only IL-6 and CRP decreased following weight loss in AA. The most distinct phenotypic difference observed was a greater impact of weight loss on TNF-α in C compared to AA, which was directly associated with IAAT in C.
Keywords: inflammation, ethnicity, diet, adiposity, visceral fat
Chronic subclinical inflammation may contribute to the pathogenesis of metabolic diseases such as type 2 diabetes, cancer, and atherosclerosis, the prevalence of which may differ with ethnicity (14). For example, it has been shown that Caucasian (C) men and women have a higher prevalence of atherosclerosis when compared to African Americans (AA) (5, 6), however it has been extensively documented that AA are more insulin resistant and are more likely to develop type 2 diabetes and hypertension (79). Whether potential differences in inflammation are associated with ethnic differences in chronic metabolic disease is not clear.
Adipose tissue is a source of pro-inflammatory cytokines, and many cross-sectional studies have shown a relationship between adiposity and circulating markers of inflammation (1012). This characteristic of adipose tissue explains in part the well-established association between obesity and chronic metabolic disease. Intra-abdominal adipose tissue (IAAT) and resident macrophages within this tissue are thought to be the primary source of cytokines relevant to metabolic disease, such as interleukin-6 (IL-6) or tumor necrosis factor-α (TNF-α). The relationship between markers of inflammation and subcutaneous adipose tissue (SAT) is less clear. Liposuction studies have shown either an improvement (13) or no effect (14) on markers of inflammation with removal of SAT. Therefore, questions still exist over the associations between markers of inflammation and abdominal fat depots.
Ethnic differences exist in body fat distribution, with C having relatively more IAAT compared to AA (5, 12). The potential role of these differences in fat distribution to inflammation and chronic metabolic disease is not entirely clear. We have previously shown that greater IAAT in C women explained their greater concentrations of circulating TNF-α and soluble cell-surface receptors (12). Several studies have shown higher concentrations of CRP (15, 16,17) and IL-6 (18) in AA compared to C, while others have shown no difference (12, 19). However, these studies did not necessarily assess fat distribution (15, 16); thus, it is difficult to conclude whether ethnic differences in fat distribution contributed to the observed differences in markers of inflammation.
Weight loss may be an effective means for reducing chronic subclinical inflammation. Intervention studies have shown that reductions in adiposity are associated with reductions in markers of inflammation (2022). However, whether AA and C respond similarly to weight loss regarding inflammation is not known. Given ethnic differences in fat distribution, it is possible that differential loss of IAAT vs other adipose compartments could affect AA and C differently. Therefore, the purpose of this study was to examine potential ethnic differences in changes in markers of inflammation with weight loss, and to identify the associations between these changes and changes in total body fat and fat distribution ((IAAT, superficial subcutaneous adipose tissue (SSAAT), deep subcutaneous adipose tissue (DSAAT)).We hypothesized that markers of inflammation would decrease to a greater extent with weight loss in C vs AA due to greater IAAT, and loss of IAAT, among C.
Subjects
Subjects were derived from a parent study involving 213 healthy, overweight, premenopausal women who volunteered for, and enrolled in a study designed to examine metabolic factors that predispose women to weight gain. The sample size included in this study was 126 women comprised of subject who both adhered to the diet requirements of the parent study and had serum samples available for analysis. 83 subjects dropped out of the study during the intervention, and plasma samples were not available for 4 subjects. Inclusion criteria for the parent study were BMI 27–30 kg/m2, premenopausal, age 20–41 years, sedentary (no more than one time per week regular exercise), normal glucose tolerance (2–h glucose ≤140 mg/dL following 75g oral dose), family history of overweight/obesity in at least one first-degree relative, and no use of medications that affect body composition or metabolism. All women were nonsmokers and reported experiencing menses at regular intervals. The study was approved by the Institutional Review Board for Human Use at the University of Alabama at Birmingham (UAB). All women provided informed consent before participating in the study.
Study design
Subjects were evaluated in the overweight state (prior to any intervention). Weight was stabilized for 4-wks prior to testing through dietary control. During the weight stabilization period body weights were measured 3–5 times per week at the General Clinical Research Center (GCRC) at UAB. During the weight maintenance period a macronutrient-controlled diet was provided by the GCRC. The energy content was appropriately adjusted to ensure a stable body weight (≤1% variation from initial body weight). All diets consisted of approximately ~ 22% of energy from fat, 23% from protein, and 55% from carbohydrate. 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 consisting of the same dietary ratios as above, 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 and/or exercise 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-wk protocol of energy balance prior to testing. All testing was conducted in the follicular phase of the menstrual cycle during a 4-day GCRC in-patient stay.
Body composition and fat distribution
Total and regional body composition, including total fat mass, percent body fat, leg fat mass, and lean body mass were measured by dual-energy X-ray absorptiometry (Prodigy; Lunar Radiation, Madison, WI). The scans were analyzed with the use of ADULT software, version 1.33 (Lunar Radiation). Intra-abdominal adipose tissue (IAAT) and subcutaneous abdominal adipose tissue (SAAT) were analyzed by computed tomography scanning (CT) (23, 24) with a HiLight/Advantage Scanner (General Electric, Milwaukee, WI) located in the UAB Department of Radiology. SAAT was further subdivided into superficial and deep compartments (25). Subjects were scanned in the supine position with arms stretched above their heads. A 5 mm scan at the level of the umbilicus (approximately the L4–L5 intervertebral space) was taken. Scans were analyzed for cross-sectional area (cm2) of adipose tissue using the density contour program with Hounsfield units for 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 <2% (24).
Laboratory analyses
All analyses were conducted in the Core Laboratory of UAB’s GCRC, Diabetes Research Training Center (DRTC), and Nutrition and Obesity Research Center (NORC). Glucose was measured using an Ektachem DT II System (Johnson and Johnson Clinical Diagnostics, Rochester, NY). In the Core laboratory, this analysis has a mean intra-assay CV of 0.61%, and a mean interassay CV of 2.56%. Insulin was assayed in duplicate 100 μl aliquots using double-antibody radioimmunoassay (Linco Research, St Charles, MO). In the Core laboratory, this assay has a sensitivity of 3.35 μIU/ml, a mean intra-assay CV of 3.49%, and a mean interassay CV of 5.57%. Markers of inflammation were assessed using enzyme-linked immunosorbent assays (ELISAs). All samples were analyzed in duplicate. TNF-α was analyzed using the high-sensitivity ELISA kit (Quantikine HSTA00C, R&D Systems, Minneapolis, MN). Four TNF-α values were below the minimum detectable concentration (0.50 pg/ml); these samples were assigned the value of the minimum detectable concentration. sTNFR-I was measured with the EASIA ELISA kit (KAC1761, Invitrogen, Carlsbad, CA). sTNFR-II was measured with the EASIA ELISA kit (KAC1771, Invitrogen). IL-6 was assayed using the high sensitivity ELISA kit (Quantikine HS600B, R&D Systems). CRP was assayed with the high-sensitivity ELISA kit (030–9710s, ALPCO, Windham, NH).
Statistical analysis
Descriptive statistics were computed for each ethnic group (AA and C) at baseline and following weight loss. All values are reported as means ± SDs. All statistical models were evaluated for residual normality and logarithmic transformations were performed when appropriate. All data were analyzed using SAS (version 9.1 SAS Institute, Cary, NC).
Comparisons between baseline and the weight reduced state were performed using the two-group t-test. Overall comparisons of the change in fat depots and markers of inflammation by ethnicity were performed using repeated-measures ANOVA. Repeated-measures mixed-models analyses were used to evaluate changes in markers of inflammation after weight loss. Independent variables included in these models were ethnicity, time, total fat mass and IAAT. For all analyses, a P value <0.05 was deemed statistically significant. There were no significant differences in any of the models after adjusting for SSAAT and DSAAT; therefore these variables were not included in the final analysis.
Baseline descriptive statistics by ethnicity are shown in Table 1. At baseline, C had significantly greater IAAT than AA. Serum concentrations of TNF-α and its receptors were higher in C than AA (Figure 1).
TABLE 1
TABLE 1
Body composition and markers of inflammation with weight loss by ethnicity
Figure 1
Figure 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 at baseline.
The effects of ethnicity, time, and the ethnicity*time interaction on all outcome variables are shown in Table 1. All markers of inflammation and adiposity decreased with weight loss. Significant ethnic differences with weight loss were observed for fat mass, body fat, IAAT, sTNF-RI, and sTNF-RII. The significant ethnicity*time interactions seen in Table 1 indicated that body weight, IAAT, and TNF-α decreased more in C than in AA.
In mixed modeling for TNF-α, there was a significant time term and a significant ethnicity*time interaction (Table 2). Adjusting for the change in IAAT not only explained the ethnic difference in change in TNF-α, but also explained the decrease in TNF-α with weight loss. Including the change in fat mass instead of IAAT explained the decrease in TNF-α with weight loss, but it did not remove ethnicity as a significant term.
TABLE 2
TABLE 2
Mixed models for TNF-α with weight loss (n=124).
In mixed modeling for sTNF-RI, there was a significant ethnicity term and a significant time term (Table 3). Adjusting for either IAAT or total fat mass explained the change in sTNF-RI with weight loss. However, there was still an ethnic difference in all models.
TABLE 3
TABLE 3
Mixed models for TNF-RI with weight loss (n=124).
Similarly, mixed modeling for sTNF-RII revealed a significant ethnicity term and a significant time term (Table 4). After adjusting for IAAT, the ethnic difference, as well as the change with weight loss, persisted. However, adjusting for total fat mass explained the change in sTNF-RII with weight loss, even though there was still an ethnic difference.
TABLE 4
TABLE 4
Mixed models for TNF-RII with weight loss (n=124).
There were no significant effects of ethnicity or ethnicity*time on IL-6 or CRP, therefore these variables were not considered for further analysis.
The purpose of this study in healthy overweight premenopausal AA and C women was to examine potential ethnic differences in markers of inflammation and regional fat distribution with weight loss, and to identify the associations between changes in these markers and changes in regional fat distribution. We found that markers of inflammation decreased following weight loss; however responses differed between AA and C women. Specifically, all markers of inflammation decreased following weight loss in C women, whereas only IL-6 and CRP decreased following weight loss in AA women. The ethnic differences observed for TNF-α between C and AA women were due in part to the greater loss of IAAT in C women. These observations suggest that there are ethnic differences among premenopausal AA and C women in the association between changes in regional fat distribution and markers of inflammation with weight loss.
We initially speculated that greater baseline IAAT and greater baseline TNF system markers among C women would result in greater changes in these measures with weight loss. We observed that C women had a greater loss of both IAAT and TNF-α with weight loss compared to AA. In fact, in C women circulating concentrations of the TNF system decreased with weight loss to levels comparable to those of their AA counterparts (Table 1). Furthermore, statistically adjusting for change in IAAT attenuated the ethnic difference in change in TNF-α (P=0.135 for ethnicity; P=0.056 for ethnicity*time interaction; Table 2). Both of these findings suggested that the change in TNF-α in C women was in part due to the loss of IAAT in this population.
We also observed an ethnic difference in the change in sTNF-RI and sTNF-RII with weight loss. C women showed decreases in both sTNF-RI and sTNF-RII, whereas AA women showed no changes in these measures. Although it is tempting to speculate that this ethnic difference was likewise attributable to greater IAAT in the C, we did not observe a significant association between the change in IAAT and the changes in the receptors. Further, inclusion of measures of body fat in the multiple regression models did not eliminate the significant effect of ethnicity.
To further probe the mechanism for the differential change in receptors between AA and C with weight loss, we examined the possibility that lean body mass played a role. Lower levels of sTNF-RI and sTNF-RII have been reported in lean compared to obese individuals (26). In our cohort, AA tended to show a preservation of lean mass with weight loss, whereas C tended to show a decrease (P=0.089 for ethnicity*time interaction; Table 1). However, when change in lean mass was included in the models for sTNF-RI and sTNF-RII, ethnicity was still a significant determinant. Thus, the mechanism through which weight loss alters the TNF receptors in C women cannot be determined from our results.
Whether a decrease in TNF receptors indicates an improvement in metabolic health is not entirely clear. TNF-α is thought to exert its biological effects on cell function by binding to cell surface receptors sTNF-RI and II (27). The extracellular portions of these receptors are present in serum as sTNF-RI and sTNF-RII, and are thought to reflect TNF-α activity. sTNF-RI is thought to mediate the metabolic actions of TNF-α, such as its effects on insulin signaling (28), while the role of sTNF-RII is less clear. These receptors are usually elevated in obese individuals compared to lean controls (26, 29, 30). However, weight loss studies have yielded equivocal results; Zahorska-Markiewicz et al. (2000) found a significant increase in both sTNF receptors following weight loss (31), while Bastard et al. (2000) found a significant decrease in sTNF-RI and no change in sTNF-RII (32). In our study, the receptors either decreased (C women) or remained unchanged (AA women). Differences among studies may be due to the energy balance status of the subjects.
In the present study we found no significant differences in IL-6 or CRP between ethnic groups at baseline or following weight loss. The parallel responses of IL-6 and CRP were not unexpected since secretion of CRP by the liver is primarily regulated by circulating IL-6 (33). The current literature examining ethnic differences in circulating IL-6 and CRP is discrepant. Cross sectional studies have reported both significant (1518), and non-significant (12, 19) differences in IL-6 and CPR between AA and C women. Visceral fat is often mentioned as the primary site of IL-6 secretion (34). However, in our sample, greater IAAT in C did not correspond to greater IL-6, suggesting that IL-6 may be released from other fat depots. This hypothesis is reinforced by the observation that adjustment for total fat but not IAAT eliminated the “time” effect in the mixed model for IL-6 (data not shown). Further, we found no significant associations of IAAT with IL-6 and CRP. While no significant associations between IAAT and IL-6 were observed, the possibility that the feedback loop involving IL-6 may not simply be related to the amount of adipose tissue but rather other stimuli can not be disregarded.
The current study revealed several areas for further evaluation. Ethnic differences have been reported for many variables, including fat distribution, insulin sensitivity, disease risk, and the TNF system. The present study also showed ethnic differences in the relationships between markers of inflammation and fat distribution. An unexamined possibility is that markers of inflammation have a different effect on adipose tissue in C vs. AA women. For example, TNF-α has autocrine functions in tissues where it is expressed, as well as more systemic paracrine functions in tissues that express the receptors for it. Because C had greater circulating TNF-α and its receptors than AA, it is possible the TNF system may be of greater physiological relevance among obese/overweight C women relative to AA.
Strengths of this study included robust measures of body composition and body fat distribution. Additional strengths included closely matching the number of AA (n = 65) and C (n = 61) women and taking post-weight loss measures after 4-weeks of weight maintenance. To our knowledge this is the first sufficiently powered longitudinal study to examine changes in regional fat distribution and markers of inflammation following weight loss among AA and C women. A limitation in this study was not examining all relevant lipid depots, such as intermuscular adipose tissue and intramyocellualar lipid. Furthermore, our results are limited to a population of healthy, overweight, premenopausal women. Similar studies on men, obese individuals, children, and postmenopausal women should be performed.
In conclusion, we demonstrated that weight loss reduces markers of inflammation in overweight premenopausal AA and C women. However, the changes in these markers following weight loss differed between ethnic groups. We found that all markers of inflammation decreased following weight loss among C, whereas only IL-6 and CRP decreased following weight loss in AA. The most distinct phenotypic difference observed in this study was a greater impact of weight loss on TNF-α in C women compared to AA women, which was directly associated with IAAT in C women. Therefore, despite the higher prevalence of some metabolic diseases in AA vs C (e.g., hypertension, type 2 diabetes), our data suggest that, regarding inflammation, weight loss may have stronger health benefit among C when compared to AA women, in part due to the greater loss of visceral fat in C women. Thus, health care providers should continue to emphasize the importance of weight loss, even among demographic groups such as young C women often assumed to be at relatively low risk for chronic metabolic disease. Further study is needed to examine the progression of low grade inflammation on the pathogenesis of chronic diseases, and how these processes differ with ethnicity
Acknowledgements
This work was supported by RO1DK51684, RO1DK49779, UL 1RR025777, P60DK079626, MO1-RR-00032, P30-DK56336, and 2T32DK062710-07. Stouffer’s Lean Cuisine and Weight Watchers Smart Ones kindly provided food used during the weight-maintenance periods. We acknowledge David Bryan and Robert Petri for technical assistance; Maryellen Williams and Cindy Zeng conducted laboratory analyses; Paul Zuckerman for project coordination.
Footnotes
Disclosure
The authors declare no conflict of interest.
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