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An independent, inverse association of high-density-lipoprotein-cholesterol concentration with nonadipose body mass^1,2,3

	ABSTRACT

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Background: Increasing body mass index (BMI) is associated with progressively lower serum HDL-cholesterol concentrations, although the underlying body-composition compartment accounting for this unfavorable lipid change remains uncertain.

Objective: Because growing evidence favors a role of lean tissue in HDL homeostasis, the hypothesis was tested that non–adipose tissue components of body mass explain the inverse association of HDL cholesterol and BMI.

Design: Fasting serum lipid concentrations and body composition [total, subcutaneous, and visceral adipose tissue; adipose tissue–free mass (ATFM); and skeletal muscle by whole-body magnetic resonance imaging and body cell mass by ⁴⁰K counting) were evaluated in healthy adults. Body-composition compartments were expressed as height²-normalized indexes.

Results: An inverse correlation was observed between serum HDL cholesterol and BMI in women (n = 68; R² = 0.08, P = 0.023) and men (n = 61; R² = 0.07, P = 0.046). Significant inverse correlations (P = 0.005–0.02) were also observed between HDL cholesterol and nonadipose components (ie, ATFM, skeletal muscle, and body cell mass) but not between HDL cholesterol and any adipose tissue component. The association between HDL cholesterol and ATFM remained significant after serum triacylglycerol was controlled for. When BMI was entered into the HDL cholesterol–ATFM regression model, BMI was not a significant independent variable. The strongest correlate of serum triacylglycerol was visceral adipose tissue (P = 0.002 for both women and men).

Conclusions: Lean tissues and body cell mass appear to account in part for the long-observed inverse association of HDL cholesterol and BMI. These observations suggest a link between nonadipose tissue compartments and the greater cardiovascular risk associated with high BMI.

Key Words: HDL cholesterol • high-density-lipoprotein cholesterol • serum lipids • cardiovascular disease • body composition • skeletal muscle • adipose tissue • body mass index • magnetic resonance imaging

	INTRODUCTION

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Cardiovascular disease is a major cause of morbidity and mortality in industrialized nations (1). Serum lipid concentrations are related to cardiovascular disease risk (1, 2) and one notable association is a statistically significant inverse correlation between HDL-cholesterol concentrations and the probability of developing coronary artery disease (3).

A major related cardiovascular disease risk factor is obesity (4, 5), and excess body weight is closely linked to low serum HDL-cholesterol concentrations (6). Large-scale studies now indicate that <5–10% of the population variation in serum HDL cholesterol can be explained by weight adjusted for height expressed as body mass index (BMI; in kg/m²) (6). Even though the between-individual variation in serum HDL cholesterol explained by BMI is small, when examined at the population level these observations are epidemiologically important.

The general assumption now is that excessive body weight is associated with enlarged adipose tissue deposits, visceral adipose tissue in particular, which in turn are accompanied by elevated serum triacylglycerol concentrations (6, 7). A well-studied inverse association exists between serum triacylglycerol and HDL-cholesterol concentrations and this may explain the observed low serum HDL-cholesterol concentrations in obesity (2, 3, 8, 9). However, whereas most studies show strong positive correlations between serum triacylglycerol concentrations and total or visceral adipose tissue (10–13), corresponding associations between various fat-containing compartments and serum HDL-cholesterol concentrations are often smaller in magnitude and less consistent (14–16).

Unlike serum triacylglycerol, which participates in fatty acid transport, cholesterol carried in HDL is directly involved in cellular sterol homeostasis; HDL may be the key carrier for reverse cholesterol transport from tissues to liver (2, 17). A link may therefore exist between lean tissues with their constituent cholesterol-rich cell mass and serum HDL-cholesterol concentrations. In support of this hypothesis, Levak-Frank et al (18) recently reported that in mutant mice expressing lipoprotein lipase (LPL) exclusively in muscle tissue, there were significant reductions in serum HDL cholesterol independent of serum triacylglycerol concentrations. Skeletal muscle LPL increases cholesterol ester uptake and this may lead to smaller HDL particles and increased HDL catabolism. The aim of the present study was to test the hypothesis that an association exists, independent of serum triacylglycerol concentrations, between serum HDL-cholesterol concentrations and non–adipose tissue body-composition components.

	SUBJECTS AND METHODS

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Study design
Fasting serum lipid concentrations (total and HDL cholesterol and triacylglycerol) and body composition were evaluated in healthy adults. The major tissue-level components that make up body weight were evaluated by whole-body magnetic resonance imaging (MRI) (19). Two main components, total-body adipose tissue and adipose tissue–free mass (ATFM = body weight - total adipose tissue), were estimated. Adipose tissue was further partitioned into subcutaneous and visceral compartments. The total-body skeletal muscle component of ATFM was also evaluated. Body cell mass was quantified from naturally occurring ⁴⁰K by using the model proposed by Moore et al (20). The 3 nonadipose tissue components evaluated included ATFM, skeletal muscle mass, and body cell mass.

Subjects
Participants were recruited from among hospital employees and students at a local university; they met the following entry criteria: age >18 y and BMI >18 and <38. An upper BMI limit was set because larger subjects do not fit in the MRI apparatus. Each participant completed a comprehensive diet and medical history questionnaire. The diet history consisted of a standard, 3-mo food-frequency questionnaire (21). Information was also gathered from subjects on potential HDL-cholesterol determinants such as medication use, cigarette smoking (22), physical activity level (23), and alcohol ingestion (21, 24). A physical examination included measurement of blood pressure, an electrocardiogram, and screening blood tests after a 12-h overnight fast.

Subjects were excluded from the study they 1) if had participated in high-intensity, structured exercise programs as evaluated by the Harvard Alumni Health Questionnaire (25), 2) had medical conditions known to affect serum lipids or body composition, 3) reported recent weight loss or weight gain (>10% of body weight within the past year), 4) had a history of drug or alcohol abuse, or 5) were taking any medications known to influence either serum lipid concentrations or body composition. Women who were postmenopausal and had received or were receiving estrogen replacement therapy were also excluded from study (26). All subjects had normal concentrations of thyroid stimulating hormone.

The study was approved by the Institutional Review Board of St Luke's–Roosevelt Hospital Center. All participants gave written consent to participate before evaluation.

Body composition
Body weight of fasting subjects wearing minimal clothing was assessed with a digital scale (Weight Tronix, New York) to the nearest 0.1 kg. Height was measured with a stadiometer (Holtain, Crosswell, United Kingdom) to the nearest 0.5 cm.

Whole-body MRI scans were prepared by using a 1.5-T scanner (model 6X Horizon; General Electric Corporation, Milwaukee) with an axial T1 weighted spin echo sequence, 10-mm slice thickness, and 40-mm interslice gap (27). Forty to fifty cross-sectional images were prepared of each subject. Adipose tissue and skeletal muscle volumes within each slice were then calculated by a single trained observer using VECT image analysis software (Martel Inc, Montreal). Total-body adipose tissue, subcutaneous adipose tissue, visceral adipose tissue, and skeletal muscle volumes were calculated from the combined cross-sectional tissue areas as reported by Ross (27). A single trained observer read all of the MRI scans. The technical errors for repeated measurements of the same scan by the same observer of adipose tissue and skeletal muscle volumes in our laboratory are ( ± SD) 1.1 ± 1.2% and 0.7 ± 0.1%, respectively (28).

Body cell mass was estimated from total-body potassium as described by Moore et al (20). Naturally occurring ⁴⁰K was quantified in a whole-body counter after a 9-min count (29). The calibration of the whole-body counter and the anthropometric body size correction protocol were reported earlier by Pierson et al (29). The system has a between-measurement technical error of 2.7% in human subjects. Total-body potassium and body cell mass were calculated as described previously (20, 29).

Lipids and lipoproteins
Serum triacylglycerol and total cholesterol were determined enzymatically by using spectrophotometric methods (30, 31). The serum HDL-cholesterol fraction was obtained after precipitation with phosphotungstic reagent (Quest Diagnostics, Teterboro, NJ). Fasting serum LDL cholesterol was calculated for descriptive purposes as described by Friedewald et al (32).

Statistical analysis
All statistical analyses were carried out by using STATVIEW software for WINDOWS (version 4.5; Abacus Concepts, Berkeley, CA). Baseline variables are described as the group mean (±SD) and between-sex differences were examined by using Student's t tests. Data were incomplete for several variables and the adjusted sample sizes are presented where appropriate.

Associations of lipid concentration and body composition were examined with serum lipid set as the dependent variable and BMI and specific body-composition components as the independent variables in simple linear regression models. Between-subject differences in stature were controlled for in body-composition regression models either by adding height (ht) as a second independent variable along with the respective component of interest or by dividing component mass by ht² to create a height-normalized index (ie, component mass in kg/ht²) (33). Regression models using absolute component mass, height and component mass, and component mass/ht² as independent variables all gave qualitatively similar results. The study observations are therefore presented only for height-normalized indexes that are consistent in expression and magnitude with BMI (33). Selected HDL multiple regression models were then developed with additional independent variables, including age, ethnicity, smoking history, daily alcohol intake, and serum triacylglycerol concentrations. Lipid–body-composition models were developed separately for women and men because of well-established sex differences in the relations of interest (34).

	RESULTS

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Subjects
The characteristics of the study population are summarized in Table 1. There was a total of 129 subjects (68 women, 61 men; 20 Asians, 33 African Americans, 67 whites, and 9 Hispanics). Women and men did not differ significantly in total cholesterol concentrations; however, women had significantly higher HDL-cholesterol (P < 0.001) and lower triacylglycerol (P = 0.001) concentrations than men.

Lipid–body composition associations
All of the following lipid–body composition associations refer to height-normalized indexes.

Triacylglycerol
The results of simple linear regression analyses are presented for serum triacylglycerol in Table 2. BMI was significantly associated with serum triacylglycerol concentrations in women (R² = 0.08, P = 0.019) and men (R² = 0.08, P = 0.030).

HDL cholesterol
The results of simple linear regression analyses are presented for HDL cholesterol in Table 3. There were significant inverse associations between BMI and HDL cholesterol in women (R² = 0.08, P = 0.023) and men (R² = 0.07, P = 0.046). No significant association was observed between HDL cholesterol and any adipose tissue component in women or men. In contrast, HDL-cholesterol concentrations were significantly inversely related to ATFM in women (R² = 0.11, P = 0.005) and men (R² = 0.10, P = 0.014). The association between HDL cholesterol and ATFM was still significant (R² = 0.19, P < 0.001) in multiple regression analyses after adjustment for possible additional lipid-related factors such as ethnicity, smoking history, physical activity level, and daily alcohol intake. When serum triacylglycerol was added as a second independent variable in regression models with ATFM, the explained HDL-cholesterol variance increased significantly in women (R² = 0.20, P < 0.001) and men (R² = 0.34, P < 0.001).

View larger version (24K): [in this window] [in a new window]   FIGURE 1. Mass of selected body compartments adjusted for height versus serum HDL-cholesterol concentration in 68 women (left) and 61 men (right). The regression line is plotted in each panel and respective regression equations are presented in Table 3. ATFM, adipose tissue–free mass; SM, skeletal muscle mass; VAT, visceral adipose tissue.

LDL cholesterol was positively correlated with all 3 adipose tissue compartments (total, subcutaneous, and visceral) in women and men. The correlation of the largest magnitude was between LDL cholesterol and total adipose tissue in women (R² = 0.19, P = 0.001) and men (R² = 0.09, P = 0.02). No significant correlations were observed between LDL cholesterol and nonadipose tissue components except for a borderline significant correlation (R² = 0.06, P = 0.052) between LDL cholesterol and ATFM in men.

	DISCUSSION

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The present study confirms many earlier observations linking serum HDL-cholesterol concentrations with BMI. As in previous investigations (35, 36), we found significant inverse correlations of small magnitude in women and men between serum HDL cholesterol and BMI. We then extended this analysis to specific body compartments, which were quantified by using whole-body MRI and ⁴⁰K counting.

Previous reports that examined associations between serum lipids and body composition focused primarily on the relations between triacylglycerol concentrations and adipose tissue compartments (8–11). Unlike the HDL-cholesterol–BMI and triacylglycerol–adipose tissue associations, earlier reports did not show a consistent link between serum HDL-cholesterol concentrations and adiposity. Some studies showed significant correlations between HDL cholesterol and adipose tissue compartments (8, 16, 37–40). In contrast, there are studies that clearly do not support an association of HDL cholesterol and adiposity. Zamboni et al (41) found significant increases in visceral adipose tissue and serum triacylglycerol concentrations with greater age that were independent of HDL-cholesterol concentrations. Hunter et al (39) similarly observed greater amounts of visceral adipose tissue and higher serum triacylglycerol concentrations in post- compared with premenopausal women and yet the older women also had higher serum HDL-cholesterol concentrations. Walton et al (15) reported that BMI and fat distribution were significantly correlated with plasma triacylglycerol (P < 0.001) but not with HDL-cholesterol concentrations. Albu et al (42) observed a strong correlation (r = 0.62, P < 0.0001) between serum triacylglycerol concentrations and visceral adipose tissue in obese women but did not detect a significant association between serum HDL cholesterol and visceral adipose tissue.

The present study results, obtained in a large subject group with use of advanced body-composition assessment methods, also did not detect a significant association between HDL cholesterol and visceral adipose tissue compartments. Rather, our findings strongly suggest that the HDL-cholesterol–BMI link is mediated instead through nonadipose components of body mass, including ATFM, skeletal muscle, and body cell mass.

Potential mechanisms
Our findings suggest an expanded view of how greater body mass is accompanied by serum lipid alterations that favor increased cardiovascular risk. As observed in this and earlier studies, with increasing BMI there are corresponding increases in both adipose and nonadipose tissue compartments such as skeletal muscle mass (29, 43). With greater adiposity, particularly visceral adiposity, there is an increase in serum triacylglycerol concentrations that is consistent across most studies (8–11), including ours. The link between excessive visceral adiposity and elevated serum triacylglycerol concentrations may be due to increased production of hepatic triacylglycerol and VLDL and reduced clearance of serum triacylglycerol via peripheral lipolysis of triacylglycerol-rich lipoproteins (44). The triacylglycerol lipolysis step, which is mediated by LPL, is sensitive to insulin action and insulin resistance, as occurs with visceral adiposity. This and other causes of slow triacylglycerol removal increase the opportunity for lipid exchange via the action of cholesterol ester transfer protein. The cholesterol ester transfer protein pathway leads to depletion of cholesterol esters in HDL and to cholesterol ester enrichment in triacylglycerol-rich lipoprotein remnants. In addition, the decrease in triacylglycerol lipolysis by LPL is accompanied by reduced availability of apolipoprotein A-I and, thus, formation of HDL precursors (2). These processes are thought to explain the observed inverse association between serum triacylglycerol and HDL-cholesterol concentrations.

The present study extends this earlier model by showing that the HDL-cholesterol–BMI association can be accounted for by nonadipose components, even after serum concentrations of triacylglycerol are controlled for. Previous animal studies suggested that subtle tissue-specific effects of skeletal muscle and cardiac muscle LPL play an important role in HDL metabolism (18). HDL composition may be altered through muscle LPL–mediated transfer of cholesterol esters from HDL to triacylglycerol-rich lipoprotein remnants (45), which leads to increased HDL catabolism. Support for this hypothesis comes from the Amsterdam Growth and Health Study, which reported that after adjustment for lifestyle and other biological factors, HDL-cholesterol concentrations were inversely related to nonfat body mass (46). A proviso of this suggested model is that our findings are largely empirical and cause-effect relations cannot be established by correlation alone. Additional mechanistic studies, guided by the present observations, are needed to firmly establish actual in vivo pathways.

Clinical implications
Taken collectively, these observations suggest that a low BMI, consisting of both low adipose tissue and nonadipose tissue components, is desirable for maintaining high HDL-cholesterol concentrations and low cardiovascular disease risk. This tentative conclusion appears contradictory to the prevailing concept that exercise, which often aims to build lean tissues such as skeletal muscle, has beneficial effects on HDL-cholesterol concentrations (47–49). An examination of this important issue, however, requires separation of aerobic exercise per se from strength-training exercise. Aerobic activities, at moderate or high intensity, are accompanied by increased concentrations of HDL cholesterol (50, 51). There are at least 2 potential explanations for this phenomenon: 1) a tendency toward reduced body mass in highly trained endurance athletes (51) and 2) accelerated catabolism of triacylglycerol-rich lipoproteins by LPL with increased HDL-cholesterol formation. Exercise also increases the key enzyme that converts HDL precursors into circulating HDL cholesterol, phosphatidylcholine–sterol O-acyltransferase (lecithin:cholesterol acyltransferase). All of these exercise-related factors collectively tend to elevate serum HDL-cholesterol concentrations.

In contrast with endurance-related activities, anaerobic exercise designed solely to hypertrophy skeletal muscles may have no effect or may even lower serum HDL-cholesterol concentrations (52–54). For example, McKillop and Ballantyne (55) observed that body builders not taking steroids had no significant differences in serum HDL-cholesterol concentrations compared with sedentary control subjects. A concern is that the available literature on this topic is limited by a lack of optimum study design and appropriate control for the important variables involved. Additionally, those interested in enlarging skeletal muscle mass beyond that obtainable by ordinary training activities often resort to anabolic steroid use. The use of anabolic steroids is associated with lowering of serum HDL-cholesterol concentrations (56, 57).

The present study results therefore pose no contradiction to prevailing concepts related to physical activity and serum HDL-cholesterol concentrations. High levels of aerobic physical activity foster a low body weight and metabolic effects that favor elevated HDL-cholesterol concentrations, whereas skeletal muscle hypertrophy produced solely by isometric activities may not have beneficial or may even have negative effects on serum HDL cholesterol.

Conclusion
The existence of a small but significant inverse correlation between serum HDL-cholesterol concentrations and BMI was confirmed in the present study. Additional analyses indicated that greater nonadipose tissue mass, including ATFM, skeletal muscle, and body cell mass, is significantly associated with lower serum concentrations of HDL cholesterol, a change in the lipid profile widely recognized as atherogenic. Adiposity, particularly visceral adiposity, was positively associated with serum triacylglycerol concentrations. Our results therefore suggest that low a BMI, consisting of both low adipose tissue and nonadipose tissue components, is important for maintaining serum concentrations of HDL cholesterol and triacylglycerol associated with minimum cardiovascular risk. Although the overall contribution of factors related to body composition to serum HDL-cholesterol concentrations in an individual subject is likely small, body mass and associated compartments contribute importantly to cardiovascular risk when considering the population as a whole and the obese population in particular. Establishing the mechanisms leading to the observed associations of body mass and serum lipids is an important future research goal.

	ACKNOWLEDGMENTS

 
We extend our appreciation to Moonseong Heo, Myles Faith, and David Allison for their guidance in preparing the statistical analyses and to Yan Xiu Tan for her technical assistance.

	FOOTNOTES

 
¹ From the Obesity Research Center, Department of Medicine, St Luke's–Roosevelt Hospital Center and Institute of Human Nutrition, Columbia University College of Physicians and Surgeons, New York, and the Department of Internal Medicine, Catholic University, Rome.

² Supported by National Institutes of Health grants RR00645 and NIDDK 42618 and a grant from the Italian Center of National Research (to AP).

³ Address reprint requests to SB Heymsfield, Weight Control Unit, 1090 Amsterdam Avenue, 14th Floor, New York, NY 10025. E-mail: sbh2{at}columbia.edu.

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