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Multiple Indexes of Lipid Availability Are Independently Related to Whole Body Insulin Action in Healthy Humans

Diabetes and Metabolism Research Program, Garvan Institute of Medical Research, St. Vincent’s Hospital, Sydney, New South Wales 2010, Australia

Address all correspondence and requests for reprints to: Dr. Adamandia D. Kriketos, Diabetes and Metabolism Research Program, Garvan Institute of Medical Research, 384 Victoria Street, Sydney, New South Wales 2010, Australia. E-mail: a.kriketos{at}garvan.org.au.

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
An increase in muscle lipid content has been postulated to relate closely to the evolution of insulin resistance. We aimed to test whether the multiple indexes of lipid supply within man [namely, circulating triglycerides, skeletal muscle triglycerides (SMT), total and central fat mass, and circulating leptin] were independent predictors of insulin resistance, or whether triglycerides from different sources are additive in their influence on whole body insulin sensitivity. Whole body insulin sensitivity, body composition, and SMT content were determined in 49 sedentary, nondiabetic males (age, 20–74 yr; body mass index, 20–38 kg/m²). Insulin sensitivity was inversely associated with central abdominal fat (r² = 0.38; P < 0.0001), total body fat (r² = 0.21; P = 0.0003), SMT content (r² = 0.16; P = 0.005), and fasting triglycerides (r² = 0.24; P = 0.0003), nonesterified free fatty acid (r² = 0.19; P = 0.002), and leptin (r² = 0.35; P < 0.0001) levels. However, only central abdominal fat was significantly related to SMT content (r² = 0.10; P = 0.03). SMT content, circulating triglycerides, and measurements of total or central adiposity were independent predictors of whole body insulin sensitivity.

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
IMPAIRED INSULIN ACTION, or insulin resistance, is associated with features of the metabolic syndrome, such as type 2 diabetes, central obesity, hypertension, and cardiovascular disease. Skeletal muscle is the primary tissue site for insulin-stimulated glucose disposal (1). Although the exact mechanisms responsible for muscle insulin resistance remain unclear, there is strong evidence that disturbances in lipid metabolism play major roles in impaired insulin action (2).

Skeletal muscle triglycerides (SMT) are a large potential energy source for muscle metabolism. It has been presumed that increased triglyceride content is indicative of increased availability of intracellular fatty acids and their derivatives, which may compete with glucose metabolism (3) and/or modulate insulin signaling pathways (4). A study by Pan et al. (5) linked impaired insulin action (assessed by insulin clamp) to increased SMT content in Pima Indians. Other studies have also shown increased muscle lipid content in patients with type 2 diabetes (6, 7) and type 1 diabetes (8) and in nondiabetic subjects with insulin resistance (9, 10). Our group has recently shown that muscle content of metabolically active, long-chain acyl-coenzyme A esters is related to whole body insulin sensitivity in both human and rodent muscle (11, 12). The exact pathway of lipid disturbance is still under investigation.

All sources of lipid availability within the body, for example, total and central fat mass and the circulating triglyceride pool, are potentially capable of affecting insulin sensitivity by supplying lipids to insulin-dependent tissues. In addition, adipose tissue produces humoral (cytokine) factors that have been suggested to affect insulin sensitivity (13, 14). Obesity, in particular central abdominal obesity (15, 16), is closely associated with insulin resistance, supporting the hypothesis that an increased supply of fatty acids can impair insulin action. Also, we have reported that improved glucose metabolism with diet-induced weight loss is specifically related to abdominal fat loss (17). In the lipid supply hypothesis, muscle lipid accumulation could occur because of both decreased fat oxidation and excess systemic fatty acid supply, leading to insulin resistance (18, 19). We investigated whether separate indexes of triglyceride within the body are independently associated with and therefore might independently contribute to the development of whole body insulin sensitivity.

The present study of 49 relatively sedentary, nondiabetic, Caucasian males, exhibiting a wide range of insulin sensitivity and adiposity, examined the influence of several indexes of lipid availability on whole body insulin resistance. Multiple regression analysis was used to clarify the independent influences of these metabolic adipose parameters on whole body insulin sensitivity. Accurate assessments of whole body insulin sensitivity (via euglycemic hyperinsulinemic clamp), body composition [dual energy x-ray absorptiometry (DEXA)], and SMT content were performed. The latter procedure included meticulous dissection of skeletal muscle biopsy specimens resulting in the removal of contaminants such as blood, fat, and connective tissue (20).

	Subjects and Methods

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Sedentary Caucasian male subjects (n = 49) were recruited from advertisements in local newspapers. The study was approved by the St. Vincent’s Hospital human research ethics committee, and all subjects gave written informed consent to participate in the study. This study was conducted according to the principles expressed in the Declaration of Helsinki.

Subjects with a history of any major illness were excluded. Before entry into the study, all subjects underwent a 75-g oral glucose tolerance test, and all were nondiabetic based on both World Health Organization and American Diabetes Association glucose tolerance criteria at the time (21, 22). No subject was taking lipid-lowering or other medications known to affect metabolism, and none was an excessive alcohol consumer. Subjects were asked to refrain from consuming alcohol for at least 24 h before testing and were studied after an overnight fast. Blood was collected at 0800 h for the measurement of plasma glucose, insulin, cholesterol, triglyceride, high density lipoprotein (HDL) cholesterol, low density lipoprotein (LDL) cholesterol, nonesterified fatty acid (NEFA), and leptin levels. This was followed by a percutaneous muscle biopsy of the vastus lateralis. Later that morning at approximately 0900 h, a euglycemic hyperinsulinemic clamp was performed, and each subject underwent a DEXA scan for assessment of body composition.

Anthropometry and body composition

For determination of body weight and height, participants wore light clothing, with footwear removed. Weight was measured to the nearest 0.1kg using a digital electronic scale. Height was measured to the nearest 0.5 cm using an anthropometer. Body mass index (BMI) was calculated as weight (kilograms) divided by height (meters) squared.

Whole body DEXA (Lunar Corp., Madison, WI; software version 1.35y) was used to analyze body composition according to a three-compartment model, comprising fat mass, lean tissue, and bone mineral content. Fat-free mass (FFM) here is defined as the sum of lean tissue and bone mineral content. Details of the measurement of central abdominal body fat have been described previously (15). Briefly, central abdominal fat mass was defined as fat mass in a window 9.8 cm in vertical dimension with the lower border at the superior iliac crest level; lateral dimensions were adjusted to the lateral borders of the costal margin. A previous report from our group has provided evidence that this central abdominal region is closely associated with insulin sensitivity, as determined by euglycemic hyperinsulinemic clamp (15). DEXA- and computed tomography-determined intraabdominal and sc fat have been shown to be similar and highly correlated (r = 0.985; P < 0.0001) (23).

Skeletal muscle biopsy

A percutaneous biopsy of the vastus lateralis muscle was obtained (50 mg) according to the method of Bergstrom (24). Upon collection, the sample was immediately blotted to remove blood, immersed in liquid nitrogen, and stored at -80 C until analyzed.

Euglycemic hyperinsulinemic clamp

Subjects underwent a 150-min euglycemic hyperinsulinemic clamp after a 12-h overnight fast as previously described (15, 25). Cannulas were inserted into an antecubital vein for the infusion of insulin and glucose (25% dextrose) and into a warmed contralateral hand vein for arterialized blood sampling. After 20 min, a baseline blood sample was collected for the determination of glucose, lipids, and hormones, and insulin was then infused (50 mU/m²·min; Actrapid HM, Novo Industries, Copenhagen, Denmark) for 150 min. A variable rate glucose infusion was used to maintain blood glucose levels close to 5 mmol/liter. The steady state glucose infusion rate (measured here over the final 30 min of the clamp) provides an index of whole body insulin sensitivity.

Skeletal muscle triglyceride content

Vastus lateralis skeletal muscle (50 mg) was freeze-dried under vacuum for 24 h. After freeze-drying, the muscle sample (15 mg) was viewed under a microscope (x6.3) at room temperature for careful dissection of muscle fibers. Traces of adipose tissue, connective tissue, and blood contamination, which could be detected by visual inspection under magnification, were removed. This procedure yielded approximately 10 mg dry weight dissected skeletal muscle, from which a direct measure of SMT content within muscle fibers was determined (20).

Total lipids were extracted according to the method of Folch et al. (26) from the dried and dissected skeletal muscle in 4 ml chloroform/methanol (2:1) and were left to rotate at room temperature overnight. Sodium chloride (0.6%) was added, and centrifugation (2000 rpm for 10min) resulted in a separation of the aqueous and organic phases. The organic phase containing the triglycerides was transferred to a glass vial and air-dried. The isolated lipids were then resuspended in 250 µl ethanol, and the triglyceride concentration was determined spectrophotometrically at 490 nm using an enzymatic colorimetric test kit (Triglycerides GPO-PAP, Roche Molecular Biochemicals, Sydney, Australia) and a Microplate Reader (model 3550-UV, Bio-Rad Laboratories, Inc., Sydney, Australia). Samples were quantitated against a standard curve of glycerol (Precimat, Roche Molecular Biochemicals) to determine SMT content.

To estimate the recovery yield after the extraction process, 2, 3, and 4 µl triolein (pure) were added to tubes containing 4 ml chloroform/methanol (2:1), and the process was completed as described above. In addition, 2, 3, and 4 µl triolein were added directly to 250 µl ethanol, and the triglyceride concentration was determined. The average yield of recovery of triolein was 98.8%. In our laboratory, the extraction of lipids from freeze-dried and carefully dissected muscle fibers and the subsequent estimation of triglyceride content are reproducible, with a within-assay variability of about 8%. From 15 subjects, 2 samples from within the same biopsy source were prepared independently and quantitated in separate assays to show the extreme possible variation between extractions. This interassay variability was 22%. In contrast, the overall between-subject variability was about 77%.

Biochemical analysis

Plasma glucose was measured by the glucose oxidase method (model 23AM glucose analyzer, YSI, Inc., Yellow Springs, OH), and plasma insulin and leptin (Human Free Insulin and Leptin RIA kits, respectively, Linco Research, Inc., St. Charles, MO) were assayed by RIA (Linco Research, Inc., Charles, MO). Serum cholesterol, HDL cholesterol, and triglyceride concentrations were determined spectrophotometrically at 490 nm using enzymatic colorimetric kits (CHOD-PAP kit, c.f.a.s. HDL-C kit, GPO-PAP kit, Roche, Basel, Switzerland). The LDL cholesterol concentration was estimated using the Friedewald formula (27). NEFA levels were measured by enzymatic colorimetry (NEFA C kit, Wako Pure Chemical Industries, Osaka, Japan). Inter- and intraassay covariances were less than 10% for these assays in our laboratory.

Statistical analysis

All values are quoted as the mean ± SD. Associations between continuous variables were investigated using simple or multiple regression analyses as appropriate. Relationships involving categorical independent variables were analyzed by ANOVA. All analyses were performed using StatView software (version 4.5, Abacus Concepts, Inc., Berkeley, CA).

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Table 1 shows the clinical and biochemical characteristics of the 49 male subjects, aged 43.7 ± 15.6 yr (range, 20–74 yr). The mean BMI was 28.5 kg/m² with a range of 20.1–37.6 kg/m². The mean SMT content was 31.7 ± 14.9 µmol/g (dry weight of tissue), spanning 3.8–67.3 µmol/g. The range of insulin sensitivity across these relatively sedentary, nondiabetic male subjects was 17.5–84.5 µmol/min·kg FFM; the mean value was 38.1 ± 14.6 µmol/min·kg FFM at a mean steady state clamp insulin level of 94.5 ± 29.9 mU/liter. Although the majority had serum lipid levels within reference adult ranges, some subjects had mild fasting hyperlipidemia.

View larger version (40K): [in this window] [in a new window]   Figure 1. Simple regression analyses between whole body insulin sensitivity (glucose infusion rate, micromoles per minute per kilogram of FFM) and indexes of lipid availability: total body fat mass (A; per kilogram per FFM), central body fat mass (B; per gram per FFM), fasting serum triglyceride concentration (C; millimoles per liter), skeletal muscle triglyceride content (D; micromoles per gram of dry weight of tissue), and fasting plasma leptin concentration (E; nanograms per milliliter).

To further characterize the interactions of indexes of lipid availability on whole body insulin sensitivity, multiple regression analyses were performed with glucose infusion rate as the dependent variable and total body fat mass (kilograms per FFM), central abdominal fat mass (grams per FFM), or fasting plasma leptin levels (as a body fatness marker) combined with circulating triglyceride levels and SMT content selected as the independent variables (Table 2). In these analyses all indexes of lipid availability were independently associated with insulin sensitivity, in combination accounting for about 45–56% of the variance in the glucose infusion rate (Table 2).

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Although excessive lipid accumulation in skeletal muscle has been shown to be associated with reduced insulin sensitivity (insulin resistance) in both type 2 diabetes and obesity in humans and rodents, this study in nondiabetic humans reports independent associations between insulin sensitivity and three measures of triglyceride supply within the body. SMT content, body fatness and circulating triglycerides were each independent predictors of insulin sensitivity, accounting for about 45–56% of the variance in insulin sensitivity in this population. This study of healthy, relatively sedentary, nondiabetic males exhibiting a wide range of BMI and whole body insulin sensitivity supports the significant indirect association between insulin sensitivity and adiposity, particularly central adiposity. Of note, SMT content was significantly related only to central adiposity and not to other measured fat depots (total body fat or circulating triglycerides). Consistent with previous reports (15, 16), the correlation coefficient for the relationship between insulin sensitivity and central fat mass (r² = 0.38) was greater than that for total body fat mass (r² = 0.21). This is consistent with the lipid supply hypothesis where the association between central (visceral and sc abdominal) fat and muscle insulin resistance (18, 28) is well established; however, the precise mechanism remains unknown. This hypothesis has also been supported by our studies of the amelioration of insulin resistance from reduced muscle (12, 29) and central fat (17) lipid supply.

Myocyte metabolism depends predominantly upon the lipid supply from intramyocellular stores and circulating triglycerides (30). Although peripheral stores are larger, central fat is more sensitive to adrenergic stimuli; it is therefore more labile and releases fatty acids more readily (31, 32, 33), with most fatty acids entering the portal vein. Increased free fatty acid turnover leads to increased very low density lipoprotein levels, decreased hepatic insulin clearance, and gluconeogenesis (34, 35, 36, 37, 38). This is consistent with our previous reports of a major relationship between central fat and insulin resistance (15, 17).

In this study we used a direct biochemical method in which to quantitatively determine SMT content from a muscle biopsy specimen. The specimen was carefully freeze-dried and dissected free from contaminants such as blood, fat, and connective tissue as described previously (20). In our hands this methodology for the determination of SMT content is reproducible with a within-assay variability of about 8%. Our absolute values for SMT content are comparable to other literature reports (39, 40), and we have shown such muscle dissection preparations to be free of adipsin mRNA expression, verifying no contamination from fat (20). More recently, magnetic resonance spectroscopy (MRS) has been used to differentiate intramyocellular lipid from extramyocellular lipid in some muscles and to relate it to insulin sensitivity in several studies (41, 42, 43, 44). However, MRS is not accessible to all laboratories, and the methodology is still being validated (45, 46). Although early results are consistent with our findings, no validation studies have been conducted between MRS-determined SMT content and that determined from the same muscle biopsy. Therefore, although more invasive, the careful assessment of SMT content from a muscle biopsy still retains an advantage over MRS assessment.

In our subject population, the highest correlation coefficient was obtained between insulin sensitivity and leptin when combined with muscle and serum triglycerides in a multiple regression model. This association could suggest a mechanistic link, as leptin has been shown to partition intracellular lipids away from triglyceride synthesis toward oxidation (47, 48, 49, 50), which by substrate competition (3), would reduce glucose utilization. However, the relationship may only reflect the very strong association of leptin with total body fat mass (51).

In addition to fasting triglycerides being associated with insulin sensitivity, there was a significant inverse relationship between fasting NEFA levels and insulin sensitivity. Fasting levels of circulating triglycerides were significantly related to NEFA levels (r² = 0.12; P = 0.018). The multiple regression analysis here includes fasting triglycerides only as an index of circulating lipids. When both plasma NEFA and triglycerides were included in the models shown in Table 2, in all cases fasting triglycerides were significant, but NEFAs were not (data not shown).

In this study we have carefully assessed insulin sensitivity, body composition, and SMT content in a healthy, nondiabetic male population with a range of adiposity and insulin sensitivity. Our findings show that whole body insulin sensitivity is independently associated with body fat, circulating triglyceride levels, and SMT content, altogether explaining about 52% of the variance of insulin action. In addition, we have shown that our general conclusions do not depend on the assumption of linearity implicit in multiple regression analysis incorporating only lean subjects (BMI, <30 kg/m²). Such findings suggest that the different sources of excess lipid could be targeted separately by future therapy. This study increases understanding of the complexity of this disorder and thus can direct further investigations and eventual therapy of insulin resistance.

	Acknowledgments

 
We acknowledge the assistance of the nursing staff of the Clinical Research Facility, laboratory technicians of the Metabolism and Diabetes Research Group, Dr. Judith Freund and technicians (Nuclear Medicine Department, St. Vincent’s Hospital Sydney), and the volunteers who participated in this study.

	Footnotes

 
This work was supported by a National Health and Medical Research Council (Australia) Peter Doherty Postdoctoral Fellowship (to A.D.K.; no. 997116) and a National Health and Medical Research Council Program Grant (Diabetes and Metabolism Research Program, Garvan Institute).

Abbreviations: BMI, Body mass index; DEXA, dual energy x-ray absorptiometry; FFM, fat-free mass; HDL, high density lipoprotein; LDL, low density lipoprotein; MRS, magnetic resonance spectroscopy; NEFA, nonesterified fatty acid; SMT, skeletal muscle triglycerides.

Received May 31, 2002.

Accepted November 14, 2002.

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