Adipocyte membrane phospholipids and PPAR-gamma expression in obese women: relationship to hyperinsulinemia

Nezha Zeghari1, Hubert Vidal2, Mohamed Younsi1, Olivier Ziegler3, Pierre Drouin3,4, and Mireille Donner1

1 Equipe Accueil 2402, Université Henri-Poincaré, 54500 Vandoeuvre les Nancy; 2 Institut National de la Santé et de la Recherche Médicale Unité 449, Faculté de Médecine Laënnec, 69000 Lyon, France; 3 Service de Diabétologie, Maladies Métaboliques et Nutrition and 4 Centre d'Investigation Cliniques Inserm-Centre Hospitalier Universitaire de Nancy, 54520 Dommartin les Toul, France


    ABSTRACT
TOP
ABSTRACT
INTRODUCTION
SUBJECTS AND METHODS
RESULTS
DISCUSSION
REFERENCES

We have shown that membrane sphingomyelin (SM) is an independent predictor of the variance of fasting plasma insulin (FPI) concentrations and the homeostasis model assessment (HOMA) estimate of insulin resistance in obese women. The peroxisome proliferator-activated receptor-gamma (PPAR-gamma ) is a key component in adipocyte differentiation that may also contribute to the sensitivity of cells to insulin. PPAR-gamma is activated by fatty acids, and the membrane composition may have an impact on the activity of PPAR-gamma and thus on the sensitivity of adipocytes to insulin. We investigated these possible links by determining the phospholipid contents of adipocyte membranes, the mRNA expression of PPAR-gamma , and the FPI and HOMA estimate of insulin resistance in obese women. The mRNA levels of tumor necrosis factor-alpha (TNF-alpha ), which is suspected to play a role in insulin resistance and which downregulates PPAR-gamma expression, were also quantified. FPI and HOMA were strongly positively correlated with membrane SM (P < 0.005) and cholesterol (P < 0.005). PPAR-gamma mRNA levels were negatively correlated with FPI (P < 0.05) and HOMA (P < 0.05) and positively correlated with high-density lipoprotein (HDL) cholesterol (P < 0.05), membrane SM (P < 0.05), and cholesterol contents (P < 0.05). TNF-alpha mRNA levels were not correlated with membrane parameters. In stepwise multiple regression analysis, the variations in PPAR-gamma mRNA levels were mainly explained by HDL cholesterol (31.9%) and membrane SM (17.7%). Our study shows that the expression of PPAR-gamma , a major factor controlling adipocyte functions, the lipid composition of the membrane, and insulin sensitivity are probably closely associated in the adipose tissue of obese women.

obesity; adipose tissue; plasma membrane; transcription factor; insulin resistance


    INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
SUBJECTS AND METHODS
RESULTS
DISCUSSION
REFERENCES

CHANGES IN THE PHOSPHOLIPID composition of the plasma membrane can dramatically alter cell functions by modifying, for example, the interactions of extracellular ligands with their receptors. Changes in membrane composition can also alter the intracellular signal transduction pathways, because the membrane contains a pool of phospholipids available for the production of second messengers. Therefore, genetically and/or nutritionally induced changes in membrane lipid composition could be involved in several human diseases (20). This is particularly relevant for the insulin resistance state, which is associated with a cluster of metabolic disturbances (42). It has been reported that there is a connection between the fatty acid composition of phospholipids in skeletal muscle and insulin sensitivity (1, 8, 10, 52). In other studies, insulin resistance has been associated with alterations in the physical properties of the membranes (12). In addition, we have shown that an altered composition of the major classes of phospholipids in erythrocyte membranes was associated with insulin resistance in obese patients. The membrane sphingomyelin content represents a major independent predictor of the variance of markers of insulin resistance in obese women (9).

Sphingomyelin also accumulates in the cell membranes in diseases with peroxisomal disorders, and it has been suggested that peroxisome proliferator-activated receptors (PPARs) are involved (46). The PPAR-gamma subtype is abundantly expressed in adipose tissue, where it plays a major role in adipocyte differentiation and in maintaining the adipocyte phenotype (47). PPAR-gamma may also play a role in the sensitivity of cells to insulin (49). This concept relies mainly on the discovery that PPAR-gamma is a high-affinity receptor for the thiazolidinediones, a class of hypoglycemic agents that enhance insulin action in target tissues (53). However, the physiological regulation of PPAR-gamma gene expression in vivo or its potential dysregulation in obesity and insulin resistance is not well characterized (5). The natural ligands of PPAR-gamma include PGJ2, a metabolite derived from arachidonic acid (17, 29). In addition, certain saturated and polyunsaturated fatty acids that are major components of cell membranes also activate PPAR-gamma (31). Therefore, the membrane composition may have important consequences for the activity of PPAR-gamma and thus the insulin sensitivity of adipocytes.

In addition to being an important constituent of cell membranes, sphingomyelin is a mediator in some of the actions of tumor necrosis factor-alpha (TNF-alpha ; see Ref. 27), a peptide that downregulates PPAR-gamma expression (54), inhibits insulin action (22, 33), and increases lipolysis (15) when added to adipose cell lines and human adipocytes. Moreover, TNF-alpha is produced by adipose tissue in proportion to the mass of fat (21, 26) and, at least in rodents, it has been demonstrated that adipose-derived TNF-alpha is a key factor in obesity-related insulin resistance (23).

Thus all of these data suggest that the expression and activity of important factors controlling adipocyte functions, the composition of the membrane, and insulin sensitivity are probably closely associated in adipose tissue. The present work was done to investigate these possible links in the subcutaneous adipose tissue of obese individuals. The distribution of cholesterol and major phospholipids in adipocyte plasma membranes and the mRNA expression of PPAR-gamma and TNF-alpha were determined in fat biopsies taken from obese women with very different body mass indexes, fasting plasma insulin concentrations, and homeostasis model assessment (HOMA) estimates of insulin resistance. PPAR-gamma and TNF-alpha mRNA levels were quantified by RT-competitive PCR (cPCR).


    SUBJECTS AND METHODS
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ABSTRACT
INTRODUCTION
SUBJECTS AND METHODS
RESULTS
DISCUSSION
REFERENCES

Selection of patients. We studied 20 obese Caucasian patients [age: 41.2 ± 2.6 yr; body mass index (BMI): 33.6 ± 0.7 kg/m2] whose body weights had been stable for several months. None of the subjects had been involved in a weight reduction program over the previous 3 mo. The glucose tolerance of the patients, based on the oral glucose tolerance test, was normal according to World Health Organization criteria. None of the subjects was treated with any drug that could influence plasma lipid concentrations or glucose tolerance. Written informed consent was obtained from all patients, and the study was approved by the Ethics Committee of the Nancy University Hospital.

Biochemical determinations. Blood samples were taken from an antecubital vein in the morning after a 12-h overnight fast. Fasting plasma glucose was measured by the glucose oxidase method with a Beckman BGA II Glucose Analyzer (Beckman Instruments, Fullerton, CA). Plasma triglycerides and cholesterol were measured enzymatically (Boehringer, Mannheim, Germany). High-density lipoprotein cholesterol (HDL cholesterol) was determined in the plasma after precipitation of very low density and low-density lipoproteins (LDL) with phosphotungstic acid. LDL cholesterol was estimated using Friedewald's formula. Plasma insulin was measured by RIA (CIS Biointernational, ORIS group, Gif-sur-Yvette, France). The sensitivity of the RIA was 1 mU/l, and the intra- and interassay coefficients of variation were 8.2 and 8.8%, respectively. The cross-reactivity with proinsulin was 14%. Fasting plasma insulin and HOMA, which is correlated with the euglycemic-hyperinsulinemic clamp (36), were chosen as insulin resistance markers. The HOMA estimate of insulin resistance was assessed by the formula [fasting insulin (mU/l) × fasting glucose (mmol/l)]22.5.

Adipose tissue biopsies. Subcutaneous fat tissue was obtained by incisional biopsy performed under local anesthesia from the lower abdominal wall. Five of 20 fat biopsies were not large enough (<5 g) for adipocyte plasma membrane preparations. Adipose tissue was frozen in liquid nitrogen immediately and was stored at -80°C.

RNA preparations. Total RNA from adipose tissue (~200 mg of frozen tissue) was obtained using the RNeasy total RNA kit (Qiagen, Courtaboeuf, France). The absorption ratio at 260 to 280 nm was between 1.7 and 2.0 for all preparations. RNA integrity was verified by agarose gel electrophoresis.

Quantification of the target mRNAs. The concentrations of PPAR-gamma and TNF-alpha mRNA were measured by RT-cPCR which, after a specific RT reaction, exploits the coamplification of the target cDNA with known amounts of a specific DNA competitor molecule added in the same PCR tube (4). The reverse transcription reactions were performed on 0.2 µg of total tissue RNA in the presence of one of the specific antisense primers. The experimental conditions, the primer sequences, and the validation of the RT-cPCR mRNA assays of PPAR-gamma and TNF-alpha have been described in detail previously (3, 6).

Adipocyte plasma membrane isolation. At first, a total membrane fraction was prepared as previously described (7), with minor modifications. Ten milliliters of a HEPES-sucrose buffer [buffer 1: 20 mmol/l HEPES, 255 mmol/l sucrose, and 1 mmol/l EDTA, pH 7.4, containing protease inhibitors (5 µg/ml leupeptin, 5 µg/ml pepstatin, and 5 µg/ml aprotinin)] were added to adipose tissue (5-7 g), and the tissue was homogenized at 4°C using an Ultra-Turrax (TP18) homogenizer. The homogenate was first centrifuged at 500 g for 10 min at 4°C. The supernatant was separated from the pellet, and fat cake and then was centrifuged at 150,000 g for 2 h at 4°C. The pellet (total membrane fraction) was then treated as previously described (34). It was suspended in buffer 1 and layered carefully on a sucrose cushion (41% in buffer 1) that was then centrifuged for 1 h at 95,000 g. The plasma membrane fraction that settled at the interface was collected, diluted in buffer 1, and washed at 4°C by centrifugation at 200,000 g for 20 min. The resulting pellet was suspended in Tris-EDTA buffer (buffer 2: 1 mmol/l Tris, 1 mmol/l EDTA, and 10 mmol/l NaCl), and the protein content was estimated by the Lowry method. The membrane suspensions obtained with this method have been characterized by use of marker enzyme activities. The plasma membrane fractions were enriched four- to sevenfold in 5'-nucleotidase activity compared with homogenized tissue. The plasma membrane fractions were stored at -80°C until further analysis.

Membrane lipid determination. Lipids were extracted from adipocyte membranes with methanol and chloroform (16) containing 50 mg/l 2,6-di-tert-butyl-p-cresol to prevent lipid peroxidation. The organic phase was evaporated to dryness under a stream of nitrogen at room temperature. The lipid residue was dissolved in chloroform, and its components were separated by HPLC (51). Lysophosphatidylcholine (10 µg/100 µg proteins) was added as internal standard before extraction. Phospholipids were detected with an evaporative light scattering detector. Phospholipid data were expressed as a weight concentration calculated from calibration curves established for each phospholipid. Membrane cholesterol was determined by the method of Zlatkis and Zak (55).

Statistical analysis. Data are presented as means ± SE or medians with 25th and 75th percentiles. Variables were assessed for normality by the skewness and kurtosis test. To improve the skewness and kurtosis of the distributions, waist-to-hip ratio (WHR), fasting blood glucose, phosphatidylcholine, and phosphatidylserine were logarithmically transformed for statistical analysis and then were backtransformed to their natural units for presentation in Tables 1-5. Medians and 25th and 75th percentiles are presented when the data follow a log normal distribution. Univariate statistical analysis was performed by linear regression analysis to identify correlations between variables. Stepwise multiple regression analysis was carried out to determine the independent predictors of PPAR-gamma mRNA levels. All calculations were performed using Statview software (Abacus Concepts, Berkeley, CA).

                              
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Table 1.   Clinical characteristics of study population


                              
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Table 2.   Cholesterol and phospholipid content of adipocyte membranes


                              
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Table 3.   mRNA levels of PPAR-gamma and TNF-alpha in subcutaneous adipose tissue


                              
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Table 4.   Pearson correlation coefficients for the relationships between insulin resistance markers and clinical characteristics, plasma lipid parameters, lipid membrane contents, and mRNA levels of PPAR-gamma and TNF-alpha


                              
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Table 5.   Stepwise multiple linear regression model for PPAR-gamma mRNA levels


    RESULTS
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ABSTRACT
INTRODUCTION
SUBJECTS AND METHODS
RESULTS
DISCUSSION
REFERENCES

The relevant clinical and metabolic characteristics of the 20 patients are shown in Table 1. Their BMIs ranged from 28 to 39.5 kg/m2. One patient had a BMI <30 kg/m2. None of the patients had major lipid abnormalities. Their fasting plasma insulin ranged from 5.2 to 40.1 mU/l. The HOMA values ranged from 1.1 to 11.8.

The mean values of cholesterol and the five classes of phospholipids of adipocyte membranes are shown in Table 2. Cholesterol ranged from 110 to 570 µg/mg proteins. Phosphatidylcholine (range: 225-1,217 µg/mg proteins) and phosphatidylethanolamine (range: 110-877 µg/mg proteins) were the more abundant phospholipids, whereas the concentrations of sphingomyelin (range: 33-167 µg/mg proteins), phosphatidylinositol (range: 21-103 µg/mg proteins), and phosphatidylserine (range: 45-276 µg/mg proteins) were less important.

The mean values of PPAR-gamma and TNF-alpha mRNA levels are shown in Table 3. For PPAR-gamma , only the total (gamma 1 + gamma 2) mRNA amount of the nuclear receptor was analyzed. PPAR-gamma mRNA concentrations ranged from 7.3 to 68.5 amol/µg total RNA. TNF-alpha mRNA was very low (0.52 ± 0.07 amol/µg total RNA).

Table 4 shows the Pearson correlation coefficients between the insulin resistance markers (fasting plasma insulin levels and HOMA values), the clinical and metabolic characteristics of the subjects, and adipocyte membrane parameters. Fasting plasma insulin correlated positively with BMI (P < 0.05), WHR (P < 0.01), fasting blood glucose (P < 0.05), membrane sphingomyelin (P < 0.005), phosphatidylcholine (P < 0.05), and cholesterol (P < 0.005) contents. The most important correlations were with sphingomyelin (r = 0.698, P <0.005) and cholesterol (r = 0.723, P < 0.005) membrane contents (Fig. 1, A and B). The correlations with the HOMA estimates of insulin resistance were similar to those observed with fasting plasma insulin, except for a positive correlation with phosphatidylethanolamine (P < 0.05) that does not exist with fasting plasma insulin. Because membrane sphingomyelin and cholesterol contents were strongly correlated with the insulin resistance markers, these two membrane components were also analyzed with regard to the anthropometric variables that characterized obesity in this study. There was no correlation with BMI or WHR.


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Fig. 1.   Relationship between fasting plasma insulin concentrations and the sphingomyelin (A) and cholesterol (B) content of adipocyte plasma membranes.

Next, we analyzed the possible relationships with the amounts of the target mRNAs (Table 4). PPAR-gamma mRNA levels were negatively correlated with the fasting plasma insulin concentrations (r = -0.470, P < 0.05), and HOMA (r = -0,482, P < 0.05) and positively correlated with HDL cholesterol (r = 0.467, P < 0.05). Figure 2, A and B, shows the correlations between PPAR-gamma mRNA levels and fasting plasma insulin and HDL cholesterol concentrations. There was also a negative correlation between PPAR-gamma mRNA levels and the amounts of sphingomyelin (r = -0.553, P < 0.05) and cholesterol (r = -0.512, P < 0.05) in the membrane (Fig. 3, A and B). The concentrations of TNF-alpha mRNA were not correlated with any other measured parameter, except with WHR (r = 0.535, P < 0.05).


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Fig. 2.   Relationship between peroxisome proliferator-activated receptor-gamma (PPAR-gamma ) mRNA levels and fasting plasma insulin (A) and high-density lipoprotein (HDL) cholesterol (B) concentration.



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Fig. 3.   Relationship between PPAR-gamma mRNA levels and the sphingomyelin (A) and cholesterol (B) membrane contents.

Stepwise multiple regression analyses were performed to evaluate the relative contribution of biological parameters and membrane lipid concentrations to the relationships with PPAR-gamma mRNA. In models with BMI or WHR, plasma lipid parameters, membrane lipid concentrations, fasting plasma insulin, or HOMA values, the variations in PPAR-gamma mRNA concentrations were mainly explained by HDL cholesterol (31.9%) and membrane sphingomyelin (17.7%; Table 5).


    DISCUSSION
TOP
ABSTRACT
INTRODUCTION
SUBJECTS AND METHODS
RESULTS
DISCUSSION
REFERENCES

We have investigated the relationship between the cholesterol and phospholipid composition of the adipocyte membranes, insulin resistance markers, and the expression of the adipose-specific nuclear receptor PPAR-gamma in subcutaneous adipose tissue in obese women.

The main phospholipids of the adipocyte plasma membrane are phosphatidylcholine and phosphatidylethanolamine, with sphingomyelin, phosphatidylserine, and phosphatidylinositol being less abundant. This phospholipid profile is compatible with data for rat adipocytes (19). The mean values of total phospholipids-to-protein (1.10 ± 0.10), phosphatidylcholine-to-protein (0.45 ± 0.06), and cholesterol-to-protein (0.26 ± 0.04) mass ratios are close to those reported for the adipocyte plasma membranes of massively obese patients (24).

Obese subjects that had a higher sphingomyelin and cholesterol content in their adipocyte membrane are less sensitive to insulin, as assessed by HOMA. These results confirm our recent observations that insulin resistance is associated with an increased sphingomyelin content in erythrocyte membranes (9). Twenty percent of the women in the obese group studied were menopausal, and none was on hormone replacement therapy. The hormonal status may influence the phospholipid composition of the adipocyte plasma membrane. It has been documented that several hormones may influence phospholipid synthesis (35, 39), but there was no correlation between age and membrane sphingomyelin content in the obese group studied, indicating that the observed differences are not likely related to the hormonal status of the patients.

As a nuclear receptor, PPAR-gamma participates in the regulation of genes involved in the differentiation of adipocytes and also in lipid metabolism (47). Its activation by the thiazolidinediones leads to the improvement of insulin action in vivo and in vitro (45). PPAR-gamma is therefore considered as playing a pivotal role in insulin sensitization and glucose metabolism (5). We find large individual variations in the amounts of PPAR-gamma mRNA in subcutaneous adipose tissue. This is in keeping with our previous data (3, 43). The variability in the amount of PPAR-gamma mRNA is not linked to the BMI of the subjects, as previously reported (43). The concentration of PPAR-gamma mRNA is positively correlated with the plasma concentration of HDL cholesterol and negatively with some markers of insulin resistance, membrane cholesterol, and sphingomyelin contents. Interestingly, in another recent study, we found a similar association between HDL cholesterol and the amounts of mRNA for PPAR-gamma subcutaneous adipose tissue (6). Nearly similar correlations in the intraperitoneal adipose tissue were also recently reported (30). The authors reported that PPAR-gamma mRNA levels were negatively correlated with fasting plasma insulin in obese nondiabetic subjects and positively with HDL cholesterol in postobese subjects. A high PPAR-gamma expression and activity may therefore be associated with a high sensitivity to insulin in the adipose tissue of obese subjects. Its is, however, important to note that this relationship between insulin resistance and adipose tissue PPAR-gamma expression has not been found when lean controls, obese nondiabetic subjects, and type 2 diabetics patients have been investigated together (43). It seems, therefore, that PPAR-gamma gene expression may be associated with insulin sensitivity in obese subjects characterized by large differences in fasting plasma insulin, sphingomyelin, and cholesterol contents of their adipocyte membranes.

There may be several links between PPAR-gamma gene expression, plasma metabolic parameters, adipocyte membrane composition, and impaired insulin action. In our study, stepwise multiple regression analysis indicated that plasma HDL cholesterol concentration could explain ~30% of the variance in PPAR-gamma mRNA levels. This relationship is supported by recent data showing that adding purified HDL particles to the culture medium stimulates human preadipocyte differentiation in vitro (50). It is possible that the induction of the expression of PPAR-gamma , a key molecular factor of this process, could be involved in the adipogenic effect of HDL. However, the mechanisms whereby plasma HDL cholesterol concentrations are related to the amounts of PPAR-gamma mRNA in adipose tissue are not yet clear. Perhaps the changes in the bidirectional transfer of cholesterol between cells and the HDL particles can participate in the regulation of the expression of the PPAR-gamma gene. In fact, HDL delivers cholesterol in an esterified form to adipocytes and removes free cholesterol from the cells. Adipocytes are enriched in the transcription factor ADD1/SREBP1c (adipocyte determination differentiation-dependent factor/sterol regulatory element-binding protein), which is activated by proteolytic cleavage after cholesterol depletion of the cell (44). Interestingly, ADD1/SREBP1c has recently been shown to regulate PPAR-gamma gene expression in cultured adipocytes, and response elements have been found in the promoter sequence of the human PPAR-gamma gene (14). Moreover, the expression of the activated form of ADD1/SREBP1c in cultured adipocytes leads to the production of ligands for PPAR-gamma (28). Therefore, the intracellular amounts of free cholesterol may be a link between plasma HDL cholesterol concentrations and PPAR-gamma gene expression in adipocytes.

Human adipocytes synthesize little cholesterol de novo: intracellular and membrane cholesterol is derived primarily from lipoproteins (2). The binding capacity of HDL to the membrane receptor (48) of adipocyte is affected by membrane lipid composition, particularly by the type of fatty acids in membrane sphingomyelin (56). In addition, the phospholipid contents of HDL particles and the cell membranes play a major role in the distribution of free cholesterol between the cell membrane and HDL (25). We have found in this study that PPAR-gamma mRNA levels are negatively correlated with the cholesterol and sphingomyelin content in the adipocyte membranes. Therefore, changes in intracellular free cholesterol could be favored by changes in the distribution of phospholipid classes, especially sphingomyelin and also cholesterol contents in the adipocyte membrane.

Differences in sphingomyelin concentration appear to explain ~17% of the variability of PPAR-gamma mRNA in the stepwise multiple regression analysis. An increased sphingomyelin content in the adipocyte membrane might also participate in PPAR-gamma gene expression through an indirect effect on the transcriptional activity of ADD1/SREBP1c. The accumulation of sphingomyelin in adipocyte plasma membranes may be due to a decreased sphingomyelinase activity, as previously reported for other cell types (13). Recently, sphingomyelinase has been reported to induce the activation of ADD1/SREBP1 through a sterol-independent mechanism (32). As discussed above, the activation of ADD1/SREBP1c could then produce ligands for PPAR-gamma and increase PPAR-gamma expression. A high sphingomyelin content in the adipocyte membrane may therefore be related to a decreased PPAR-gamma gene expression and activity through this mechanism.

TNF-alpha was another candidate for the link between insulin resistance and lipid composition of the membrane. In fact, the intracellular action of TNF-alpha involves, at least in part, plasma membrane sphingomyelin to generate ceramide (27). In addition, TNF-alpha in cultured adipose cells leads to a decreased expression of PPAR-gamma in cultured adipose cells (54). Some data have also suggested that increased expression of TNF-alpha in adipose tissue might be associated with insulin resistance during obesity (23, 26). In agreement with recent works (6, 38), we found extremely low concentrations of adipose TNF-alpha mRNA, even in fat samples from extremely obese women. There was no correlation between subcutaneous adipose tissue TNF-alpha mRNA levels and the phospholipid composition of the adipocyte membrane, insulin resistance markers, or the BMI in the studied obese women. This extremely low level of expression of TNF-alpha was consistent with the lack of significant in vivo production of the cytokine by human adipose tissue in obese subjects (37). These results do not, however, exclude the possibility that TNF-alpha plays a role in insulin resistance in humans. In fact, elevated concentrations of circulating TNF-alpha have been found in insulin-resistant obese patients with and without type 2 diabetes mellitus (11, 40, 41). However, it is likely that plasma TNF-alpha does not originate from adipose tissue in these situations.

In conclusion, our findings in the adipocytes of insulin-resistant obese patients pointed to a potentially important role for sphingomyelin and cholesterol in the membrane. Because strong interactions exist between the cholesterol and sphingomyelin contents of the adipocyte membranes, those that are enriched in cholesterol are also enriched in sphingomyelin (18). It is likely that cholesterol levels in the membrane reflect the intracellular cholesterol concentration, which may in turn affect the regulation of the expression of several important genes, including the gene for the nuclear receptor PPAR-gamma . Differences in membrane cholesterol content between obese individuals may then affect both the structural membrane properties and the function of the adipocytes, two effects that may contribute to modifications of insulin action. It is now important to discover what determines the difference in cholesterol content of the adipocyte membrane between obese individuals. The altered metabolism of lipoproteins and the interaction of HDL with cell membranes are presently being investigated.


    ACKNOWLEDGEMENTS

We thank Drs. Saury and Dinh Doan for help in performing the biopsies. The English text was corrected by Dr. Owen Parkes.


    FOOTNOTES

This work was supported in part by a grant from the Association de Langue Française pour l'Etude du Diabète et des Maladies Métaboliques-Institut Servier du Diabète, 1997 and the Fondation pour la Recherche Médicale.

Address for reprint requests and other correspondence: M. Donner, EA 2402, Bâtiment INSERM, CHU de Brabois 54511, Vandoeuvre les Nancy Cédex, France (E-mail: donner{at}u14.nancy.inserm.fr).

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 21 October 1999; accepted in final form 2 May 2000.


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TOP
ABSTRACT
INTRODUCTION
SUBJECTS AND METHODS
RESULTS
DISCUSSION
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