Women with previous gestational diabetes (pGDM) are frequently insulin-resistant, which could relate to intramyocellular lipid content (IMCL). IMCL were measured with 1H nuclear magnetic resonance spectroscopy in soleus (IMCL-S) and tibialis-anterior muscles (IMCL-T) of 39 pGDM (32 ± 2 years, waist-to-hip ratio 0.81 ± 0.01) and 22 women with normal glucose tolerance (NGT; 31 ± 1 years, 0.76 ± 0.02) at 4–6 months after delivery. Body fat mass (BFM) was assessed from bioimpedance analysis, insulin sensitivity index (SI), and glucose effectiveness (SG) from insulin-modified frequently sampled glucose tolerance tests. pGDM exhibited 45% increased BFM, 35% reduced SI and SG (P < 0.05), and 40% (P < 0.05) and 55% (P < 0.005) higher IMCL-S and IMCL-T, respectively. IMCL related to body fat (BFM P < 0.005, leptin P < 0.03), but only IMCL-T correlated (P < 0.03) with SI and glucose tolerance index independent of BMI. Insulin-resistant pGDM (n = 17) had higher IMCL-S (+66%) and IMCL-T (+86%) than NGT and insulin-sensitive pGDM (+28%). IMCL were also higher (P < 0.005, P = 0.05) in insulin-sensitive pGDM requiring insulin treatment during pregnancy and inversely related to the gestational week of GDM diagnosis. Thus, IMCL-T reflects insulin sensitivity, whereas IMCL-S relates to obesity. IMCL could serve as an additional parameter of increased diabetes risk because it identifies insulin-resistant pGDM and those who were diagnosed earlier and/or required insulin during pregnancy.

Gestational diabetes mellitus (GDM) is a frequent metabolic complication during pregnancy that does not completely normalize after delivery (13). Women with a history of previous gestational diabetes (pGDM) are often insulin-resistant and exhibit markedly increased risk for the later development of type 2 diabetes (4,5). The most prominent parameters that predict type 2 diabetes in later life are the need for insulin in addition to diet therapy to achieve normoglycemia, early diagnosis of GDM during pregnancy, and maternal BMI and plasma glucose during the oral glucose tolerance test (OGTT) at diagnosis as well as at the first postpartum assessment (4,6,7).

Skeletal muscle insulin resistance is a key feature of the metabolic syndrome and predisposes to type 2 diabetes and premature cardiovascular complications (8). Although lifestyle (9), obesity, and increased lipid supply play an important role in this disease (8,10), the hierarchy of events is still unclear. It was postulated that muscle fat content could contribute to insulin resistance and glucose intolerance (1119), but only the advent of 1H nuclear magnetic resonance spectroscopy (NMRS) made it possible to quantify and distinguish between extramyocellular and intramyocellular lipid contents (IMCL) (11,14,15,17,18,2022).

We tested the hypotheses that intracellular fat content in different muscles diversely relates to insulin sensitivity and correlates with established risk markers for type 2 diabetes in pGDM, such as gestational week at diagnosis, insulin treatment during pregnancy, glucose levels during OGTT at diagnosis and postpartum, and the degree of obesity. Thus, we applied 1H NMRS to measure rapidly and noninvasively IMCL in soleus (IMCL-S) and tibialis anterior muscles (IMCL-T) in pGDM. IMCL were correlated with parameters of glucose tolerance, insulin sensitivity, cardiovascular risk, body fat content, and distribution. Furthermore, the study extends to potential links between IMCL and the leptin system, which participates in the regulation of body weight (BW) and energy metabolism (19,23,25,26).

All women ingested an isocaloric diet containing 200 g of carbohydrates/day and refrained from exercise for at least 3 days before the studies. Metabolic tests were performed on different days during the first phase (days 5–8) of the menstrual cycle after 10- to 12-h overnight fasting.

Study participants.

Cross-sectional analysis was performed in 39 pGDM women at 4–6 months after delivery. They were recruited from our division’s outpatient service, where they had been seen previously during pregnancy. GDM had been diagnosed according to the criteria of the 4th Workshop Conference of Gestational Diabetes (27). During pregnancy, 26 women were treated with diet plus insulin, because blood glucose exceeded 95 mg/dl at fasting and/or 130 mg/dl at 60 min postprandially. A total of 22 age-matched women without any risk for diabetes and with normal glucose tolerance during pregnancy served as a control group (NGT). All subjects gave written informed consent for participation in the study, which was approved by the local ethics committee.

Patients with previous ketoacidosis and/or β-cell antibodies (GAD, ICA, IA2) were excluded. The relationship among IMCL, insulin sensitivity, and metabolic parameters was analyzed both in the total pGDM population and for the insulin-sensitive (pGDM-S) and insulin-resistant subgroups (pGDM-R), which were separated by a cutoff value of 2.8 10−4 min−1/(μU/ml) for the insulin sensitivity index (SI). This value was derived from analyzing SI of the NGT of the present study plus another 26 matched female control subjects from other studies. The lower 2.5% quantile of the distribution gave an SI of 2.79 10−4 min−1/(μU/ml), which was defined as the cutoff point between normal and impaired (lower) SI.

All pGDM had higher waist circumference, diastolic blood pressure, HbA1c, and basal metabolic rate corrected for BW than NGT (Table 1). After correction for BMI, differences in waist-to-hip-ratio disappeared, whereas waist circumference remained different (P < 0.01).

Clinical characteristics were not different between NGT and pGDM-S except for HbA1c (Table 1). In contrast, pGDM-R had higher BMI and systolic blood pressure but lower HDL cholesterol. Basal metabolic rate adjusted for BW was lowest in pGDM-R (−16% versus NGT and pGDM-S) but not different between pGDM-S and NGT. After correction for lean body mass, i.e., fat-free mass (FFM), the basal metabolic rate was not different between pGDM (30.50 ± 0.33 kJ/kg FFM) and NGT (30.57 ± 0.39 kJ/kg FFM) but lower in pGDM-R (29.35 ± 0.50 kJ/kg FFM) than pGDM-S (31.58 ± 0.42 kJ/kg FFM, P < 0.003) and NGT (P < 0.03).

Frequently sampled intravenous glucose tolerance test.

Glucose (time 0–0.5 min: 300 mg/kg BW) and then normal insulin (time 20–25 min: 0.03 IU/kg, Humulin R; Eli Lilly, Indianapolis, IN) were infused intravenously, and venous blood samples were taken in timed intervals (28). Analysis of glucose and insulin concentrations provided indexes for glucose tolerance (KG), insulin sensitivity (SI), and glucose effectiveness (SG), which describe glucose disposal and the insulin effect on glucose disappearance (28). Insulin secretion was assessed from incremental short-term insulin response (ΔAIRG) calculated by averaging insulin concentration above basal from times 3–10 min. The disposition index was calculated as SI times ΔAIRG and gives a measure of the combined effects of insulin secretion and sensitivity on glucose disposal (29).

OGTT.

Participants ingested 75 g of glucose solution, and venous blood samples were collected for glucose, insulin, and C-peptide measurements at timed intervals (30). Modeling analysis yielded fasting prehepatic insulin secretion rate and the total amount of insulin per unit volume released during the OGTT in response to increments in glucose concentration (30). Insulin sensitivity from OGTT (OGIS) was derived as glucose clearance (ml · min−1 · m−2) (31).

Localized 1H NMRS.

IMCL was measured with localized 1H NMRS (17,20,21) on a 3.0-T/80-cm NMR spectrometer (Medspec; Bruker, Ettlingen, FRG) equipped with a whole-body gradient coil (40 mT/m; Fig. 1). A standard birdcage 1H coil (inner diameter 25 cm) was used in the transmission/reception mode. The STEAM sequence (echo time 20 ms; mixing time 30 ms; relaxation time 6 s; number of scans 32) was complemented by CHESS water suppression and applied on the 1.73-cm3 volume of interest, which was placed in the soleus or tibialis anterior muscles of the subject’s right leg. Spectra were line-broadened and -fitted using the MacNUTS-PPC software (Acorn NMR, Livermore, CA). IMCL was quantified from processed spectra after T2-relaxation correction as a ratio of the intensity of (CH2)n (1.25 ppm) group resonance to the intensity of the water resonance from non-water-suppressed spectra of the same volume of interest (Fig. 1). The T2 relaxation times were of 82 ± 3 ms for IMCL-S and 30 ± 2 ms for water in soleus muscle and 90 ± 6 ms for IMCL-T and 27 ± 1 ms for water in tibialis anterior muscle. The coefficients of variation for 1H NMRS of IMCL, as assessed from three measurements of the lipid content in each muscle in six healthy young subjects, were 0.3% for soleus muscle and 1.3% for tibialis anterior muscle, respectively.

Body fat mass and basal metabolic rate.

Body fat mass (BFM) was assessed from bioimpedance measurements (Akern-RJL Systems, Florence, Italy) as was the basal metabolic rate. Measurement of resting energy expenditure with bioimpedance was validated in 10 subjects against indirect calorimetry yielding comparable results (r = 0.78, P < 0.01). Resting energy expenditure is expressed per kg BW as well as per kg FFM.

Metabolites and hormones.

Plasma glucose was measured using an automated glucose analyzer (Beckman, Fullerton, CA). HbA1c (upper limit of normal range 5.8%) was quantified by online high-pressure liquid chromatography (C-R4A Chromatopac; Shimadzu, Kyoto, Japan) from capillary blood. Cholesterol and triglyceride concentrations were measured by lipid gel electrophoresis. Insulin (Serono Diagnostics, Freiburg, FRG), C-peptide (CIS Bio International, Cedex, France), proinsulin, and total leptin (both from Linco, St. Charles, MO) were quantified in duplicate by radioimmunoassays with interassay coefficients of variation of <5.5% for insulin, C-peptide, leptin and <8% for proinsulin. Plasma bound leptin and soluble leptin receptor concentrations were measured by specific radioimmunoassay (25,26,32). Fasting plasma free fatty acids (FFA) were measured as described (33) and available in most pGDM (n = 30) and NGT (n = 17).

Statistical analysis.

Data are presented as means ± SE. Relationships were tested for statistical significance by linear regression analysis and Spearman correlation coefficient. Groups were compared with nonparametric ANOVA, and multiple test statistics were used for subgroup analyses comparing NGT, pGDM-R, and pGDM-S (SAS package, version 8.2, Tukey-Kramer). ANOVA was also performed including interaction between groups and BMI or BFM. In the absence of significant interaction, groups were also compared after correction for BMI or BFM. Multiple regression analysis was computed to identify independent regulators of IMCL.

One woman in the pGDM-R subgroup had an IMCL-T value within the range of the other pGDM, whereas her IMCL-S value of 7.7% H2O resonance exceeded the interquartile range (five times above the 75% quartile of all pGDM-R, more than seven times above that of the total population) and was therefore excluded from analysis. Nevertheless, inclusion or exclusion of this outlier did not affect the statistically significant differences.

Glucose metabolism.

All pGDM featured lower SI (−35%), glucose effectiveness (SG −25%), and disposition index, a marker of overall glucose homeostasis (−47%), than NGT (Table 2). In the subgroup, pGDM-R, SI was even 70 and 65% lower than in NGT and pGDM-S, respectively (Table 2). The disposition index was lower in pGDM-R than in NGT but not different between pGDM subgroups. The glucose tolerance index (KG) was >30% lower in all pGDM, whereas ΔAIRG was 22% lower only in pGDM-S, reflecting reduced insulin release in response to a given glucose load. In contrast, pGDM-R featured 50% higher ΔAIRG than in NGT, indicating compensation by the β-cells for their insulin resistance.

Although fasting and postprandial plasma glucose concentrations during OGTT were higher in pGDM, no woman was diabetic according to American Diabetes Association and World Health Organization criteria (Table 2). The insulin sensitivity index (OGIS) was reduced by 10 and 25% in pGDM-S and pGDM-R, respectively. The pGDM-R compensated their marked insulin resistance by doubling basal and dynamic insulin secretion, which in contrast were not different between pGDM-S and NGT. Correction for BMI or BFM as a result of the higher degree of obesity in pGDM-R did not affect the differences in insulin sensitivity (P < 0.001) and glucose effectiveness (P < 0.05) between groups. Fasting plasma FFA were higher in both the total group of pGDM (0.63 ± 0.04 μmol/l, P < 0.005) and the subgroups (P < 0.01) pGDM-R (0.61 ± 0.09 mmol/l) and pGDM-S (0.60 ± 0.05 mmol/l) than in NGT (0.38 ± 0.03 mmol/l) but did not differ (P = 0.07) between subgroups.

IMCL.

Mean IMCL-S and IMCL-T were 31 and 61% higher in the total group of pGDM than in NGT (Table 3). In the subgroup pGDM-R, both IMCL were also higher (IMCL-S 66%; IMCL-T 86%) than in NGT and one third higher in pGDM-R than in pGDM-S. Also, BFM was 78 and 56% higher in GDM-R than in NGT and GDM-S, respectively (Table 3). After correction for either BMI or BFM, the differences in IMCL-S disappeared (P = 0.10 for BMI, P = 0.61 for BFM), whereas IMCL-T remained increased in pGDM-R (P = 0.01 for BMI, P = 0.04 for BFM), indicating that obesity strongly influences only IMCL-S.

Nearly all pGDM-R (n = 15 of 17; 88%) but only 50% of GDM-S (n = 11 of 22) had required insulin therapy during pregnancy. The pGDM-S treated previously with insulin presented with higher IMCL-S (P < 0.005) and IMCL-T (P = 0.05) than insulin-naive patients who were treated with diet despite no difference in metabolic or anthropometric parameters (Fig. 2).

Leptin system.

Plasma total leptin was highest in pGDM-R (Table 3). The fraction of bound leptin was not different between pGDM-R and NGT but was 50% lower in pGDM-S. However, when adjusted for BFM (Table 3) and corrected for BMI, bound leptin became markedly (P < 0.001) different, being lower in both GDM subgroups than in NGT. Plasma concentrations of soluble plasma leptin receptor were decreased in pGDM independent of BMI, whereas total leptin was no more different between groups after correction for BMI.

Correlation analysis.

In all women, IMCL correlated positively with BMI and BFM and negatively with the basal metabolic rate after adjustment for BW (Fig. 3). However, when expressed per FFM, basal metabolic rate did not relate to IMCL-S or IMCL-T (P = 0.09) but still to IMCL-T in pGDM-R (r = −0.55, P < 0.04). IMCL was also associated with 2-h plasma glucose during OGTT (Fig. 4), waist circumference (r = 0.4, P < 0.001), plasma total leptin (r = 0.32, P < 0.03), and plasma FFA (IMCL-S: r = 0.31, P < 0.03; IMCL-T: r = 0.55, P < 0.001). In all women, IMCL also inversely related to the gestational week during which GDM was diagnosed (IMCL-S r = −0.30, P < 0.05; IMCL-T r = −0.44, P < 0.02), but only IMCL-T also negatively related to systolic blood pressure and negatively correlated with SI, SG, and KG (r = −0.31, P < 0.03; Fig. 4). In pGDM-R, IMCL-T negatively related to the disposition index derived from both intravenous (r = 0.62, P < 0.02) and oral glucose challenge (r = −0.67, P < 0.014; Spearman, ANOVA). Multiple regression analysis including SI, BMI, and 2-h plasma glucose as explanatory variables showed that for IMCL-S only BMI and for IMCL-T only the 2-h plasma glucose had an independent influence. With only BMI and SI in the model, SI remained as the only significant independent parameter to explain IMCL-T. When BFM entered the multiple regression analysis instead of BMI, again only BFM influenced IMCL-S (P < 0.02), and 2-h plasma glucose (P < 0.04) and BFM (P < 0.05) influenced IMCL-T. With only BFM and SI in the model, BFM still significantly affected IMCL-S (P < 0.01), whereas no parameter independently affected IMCL-T.

Linear regression analysis for plasma leptin revealed its correlation to BMI (r = 0.70, P < 0.0001), waist-to-hip ratio (r = 0.40, P < 0.003), 2-h glucose during OGTT (r = 0.45, P < 0.002), systolic and diastolic blood pressures (r = 0.38, P < 0.009), triglycerides (r = 0.30, P < 0.05), HDL cholesterol (r = −0.31, P < 0.03), insulin sensitivity (r = −0.30 P < 0.04), and insulin secretion (r = 0.38, P < 0.009). In contrast, bound leptin correlated inversely only with 2-h glucose (r = −0.30, P < 0.03) and positively with the soluble leptin receptor (r = 0.53, P < 0.005) as well as parameters of glucose effectiveness (r = 0.33, P < 0.01) and insulin sensitivity (r = 0.43, P < 0.001). Soluble leptin receptor concentrations were inversely related to IMCL-T (−0.43, P < 0.05) and positively to HDL cholesterol (r = 0.57, P < 0.02).

This study confirms that the disturbances in glucose metabolism persist in women with pGDM. Of the present population, 44% were severely insulin-resistant (pGDM-R) with excessive insulin secretion and higher degree of abdominal fat as indicated by their higher waist circumference and waist-to-hip ratio than the other groups. However, 56% were insulin-sensitive (pGDM-S) but showed distinct abnormalities of early and dynamic insulin secretion during intravenous and oral glucose challenge. Both metabolic abnormalities resulted in similarly higher plasma glucose in both pGDM subgroups than in NGT.

Although parameters of long-term glucose control such as plasma glucose during OGTT and HbA1c were comparable at 4–6 months after delivery, almost all pGDM-R and half of the lean pGDM-S had required insulin therapy during pregnancy. Glucose control was similar throughout pregnancy between pGDM-S and pGDM-R as reflected by HbA1c and self-recorded daily pre- and postprandial glucose profiles. As the requirement of insulin therapy indicates a more severe derangement of glucose metabolism and is considered an important risk factor for the progression to overt diabetes, it seems that pGDM-R are at higher risk of type 2 diabetes than pGDM-S. It is of note that these women with characteristic features of the metabolic syndrome also presented with highest IMCL. Moreover, even the 50% of pGDM-S on previous insulin therapy had higher IMCL than the insulin-naive pGDM-S whose IMCL were almost identical to those of NGT. As increased IMCL was the only parameter that differed in these pGDM-S subgroups, it might be an important marker to identify even women who are lean and otherwise insulin-sensitive but at increased risk for type 2 diabetes. Furthermore, in all pGDM, independent of their insulin sensitivity, the higher IMCL was related to earlier diagnosis of GDM, another widely known risk factor for deterioration of glucose tolerance at follow-up (6).

IMCL was higher in GDM-R than in the other groups and correlated with body fat, insulin sensitivity, and cardiovascular risk parameters in all women. Thus, increased IMCL may be added to the characteristics of the metabolic syndrome. Previous studies reported divergent results on the relationship between IMCL and anthropometric parameters (34,35), which possibly results from differences between individual skeletal muscle groups.

We found that IMCL-S more strongly relate to measures of obesity, whereas IMCL-T are more tightly associated with insulin resistance per se. This is in line with one report (11) but partly in contrast to another study reporting a better correlation of insulin resistance with IMCL-S and increased IMCL-T only in women (20). Although the correlation of IMCL-S with the degree of obesity might suggest that increased intracellular muscle fat simply reflects whole-body adiposity, the correlation of IMCL-T with parameters of the insulin resistance syndrome was found to be independent of BMI. In untrained humans, skeletal muscle represents a mixed fiber type (36) containing fiber types of different insulin sensitivity (37). Soleus muscle is prevalently composed of slow-twitch oxidative type I fibers, whereas tibialis anterior muscle contains more fast-twitch glycolytic type IIb fibers. Type I fibers generally have a higher lipid content yet also higher oxidative enzyme capacity and greater insulin sensitivity than type IIb fibers (38). In obesity and type 2 diabetes, the proportion of type IIb fibers with reduced oxidative enzyme activity may increase (39,40) so that a dynamic interaction between fiber type and metabolic capacity with more lipid stored in relation to oxidative capacity can be postulated for metabolic disorders. Furthermore, reduction of type I fibers with decreased expression of insulin sensitive glucose transporters (GLUT4) was detected in type 2 diabetes (41).

At present, a cause-effect relationship for IMCL and insulin sensitivity is not clear and the mechanisms of interaction are not yet fully understood. Plasma FFA resulting from dietary fat supply and/or increased lipolysis in fat tissue may directly induce insulin resistance or could be channeled preferentially into triglycerides (8,10,19,42,43). Increased FFA uptake or lipolysis of IMCL would increase cytosolic long-chain acyl-CoA (LCA-CoA), which correlate well with insulin resistance (43) and can inhibit insulin action via decreased insulin-receptor substrate-1 phosphorylation (42,43). In line with this hypothesis, plasma FFA elevation induces insulin resistance and gives rise to IMCL under high (21,44) but not fasting insulin conditions (33). Likewise, improvement of insulin resistance by the thiazolidinedione pioglitazone reduces muscle LCA-CoA and lipid accumulation in high-fat-fed rats (45) so that the beneficial effect of troglitazone to improve insulin action and reduce progression to type 2 diabetes in high-risk Latino women with pGDM (46) could at least partly result from altered muscle lipid supply.

Alternatively, the correlation between IMCL-T and 2-h plasma glucose during OGTT hints at an interaction between postprandial hyperglycemia and IMCL. Kelley et al. (47) proposed the concept that provision of glucose inhibits lipid oxidation, which could contribute to pathogenesis of lipid accumulation in obesity. In contrast to the present study, Phillips et al. (15) detected no correlation between 2-h plasma glucose and IMCL as measured from muscle biopsies of women at a mean age of 52 years. Cross-sectional studies in other populations (11,12,20,22) found no significant correlation for fasting plasma glucose and IMCL. We have previously reported that short-term hyperglycemia for 2 h in the presence of fasting (peripheral) insulinemia increases glucose disposal without changes in IMCL-S (33). Nevertheless, it cannot be excluded that chronic postprandial increases in plasma glucose may contribute to IMCL accumulation in pGDM.

The close association between IMCL and elevated plasma total leptin concentrations correlating with insulin secretion, insulin resistance, and BFM in pGDM could point at increased weight retention postpartum (48,49) and risk for later type 2 diabetes (50,51). In the present study, increased total leptin was mostly explained by increased free leptin, because bound leptin and soluble leptin receptor were even lower in pGDM. Of note, the bound form was positively associated with glucose disposal and tolerance, whereas the soluble leptin receptor was inversely related to IMCL-T. The soluble leptin receptor represents the major leptin binding protein in human blood and may therefore determine the circulating amount of total leptin (26,52). It was postulated that the bound form is involved in the regulation of energy expenditure, whereas the free form simply reflects the degree of adiposity (25,32). The present study supports this hypothesis, because the degree of adiposity explains variations in plasma total leptin, whereas the protein-bound form and the soluble leptin receptor were similarly reduced in all pGDM after correction for BFM.

In conclusion, IMCL-T as measured with 1H NMRS reflects insulin sensitivity and glucose homeostasis, whereas IMCL-S predominantly relates to the degree of obesity in women with pGDM. Increased IMCL particularly identifies those women who are markedly insulin-resistant and/or require insulin during pregnancy and who receive a diagnosis earlier in the course of pregnancy. Thus, higher IMCL relate to classical risk factors for type 2 diabetes in this cohort of young women and could be added to features of the metabolic syndrome and serve as an additional marker of risk for later type 2 diabetes in women with pGDM.

FIG. 1.

Left: Magnetic resonance cross-sectional image of human calf muscle. The rectangles indicate the positioning of the volumes of interest in soleus and tibialis anterior muscles. Right: 1H NMR spectra acquired from the volumes of interest in both muscles.

FIG. 1.

Left: Magnetic resonance cross-sectional image of human calf muscle. The rectangles indicate the positioning of the volumes of interest in soleus and tibialis anterior muscles. Right: 1H NMR spectra acquired from the volumes of interest in both muscles.

FIG. 2.

Box plots for IMCL-S and IMCL-T in insulin-sensitive women who had pGDM-S and were treated by diet (n = 11) or insulin (n = 11) during pregnancy. The median is represented by the horizontal line inside the box; the top and bottom of the box represent the third quartile (75th percentile) and the first quartile (25th percentile), respectively. Whiskers are drawn from the edge of the box to the farthest observation within 1.5 times the interquartile range of the edge of the box. Observations beyond the whiskers are individually identified (•).

FIG. 2.

Box plots for IMCL-S and IMCL-T in insulin-sensitive women who had pGDM-S and were treated by diet (n = 11) or insulin (n = 11) during pregnancy. The median is represented by the horizontal line inside the box; the top and bottom of the box represent the third quartile (75th percentile) and the first quartile (25th percentile), respectively. Whiskers are drawn from the edge of the box to the farthest observation within 1.5 times the interquartile range of the edge of the box. Observations beyond the whiskers are individually identified (•).

FIG. 3.

Relationship between BMI, fat mass (FAT), and basal metabolic rate adjusted for BW and IMCL-S and IMCL-T in all women by linear regression analysis.

FIG. 3.

Relationship between BMI, fat mass (FAT), and basal metabolic rate adjusted for BW and IMCL-S and IMCL-T in all women by linear regression analysis.

FIG. 4.

Relationship between 2-h plasma glucose concentrations during the OGTT (OGTT2 h), the insulin sensitivity index (SI) from frequently sampled insulin modified intravenous glucose tolerance tests (FSIGT) and the systolic blood pressure and intramyocellular lipid content in soleus muscle (IMCL-S) and in tibialis anterior (IMCL-T) in all women by linear regression analysis.

FIG. 4.

Relationship between 2-h plasma glucose concentrations during the OGTT (OGTT2 h), the insulin sensitivity index (SI) from frequently sampled insulin modified intravenous glucose tolerance tests (FSIGT) and the systolic blood pressure and intramyocellular lipid content in soleus muscle (IMCL-S) and in tibialis anterior (IMCL-T) in all women by linear regression analysis.

TABLE 1

Clinical characteristics of the total group of women with pGDM (n = 39), the insulin-resistant subgroup (GDM-R, n = 17), and the insulin-sensitive subgroup (GDM-S, n = 22) compared with women with NGT during pregnancy (n = 23) 4–6 months after delivery

GDMGDM-RGDM-SNGT
Age (years) 31.1 ± 0.81 31.0 ± 1.4 31.2 ± 1.0 30.6 ± 1.3 
BMI (kg/m226.4 ± 1.1 29.8 ± 1.8 24.9 ± 0.8* 24.3 ± 0.9 
WHR 0.81 ± 0.01 0.81 ± 0.01 0.80 ± 0.01 0.76 ± 0.02 
Waist (cm) 89.1 ± 2.3§ 96.1 ± 2.5 84.5 ± 2.2* 75.1 ± 2.3 
Triglycerides (mg/dl) 118.2 ± 22.0 136.3 ± 50.9 105.9 ± 14.3 75.2 ± 6.3 
Cholesterol (mg/dl) 210.9 ± 7.6 200.3 ± 14.1 218.0 ± 8.3 198.0 ± 12.4 
HDL cholesterol (mg/dl) 61.4 ± 2.7 54.8 ± 4.7 65.8 ± 3.9* 62.1 ± 2.9 
LDL cholesterol (mg/dl) 126.2 ± 6.5 118.9 ± 10.9 131.2 ± 7.9 120.8 ± 11.0 
Systolic blood pressure (mmHg) 116.7 ± 2.2 123.7 ± 3.9 112.3 ± 2.3* 111.5 ± 2.6 
Diastolic blood pressure (mmHg) 80.0 ± 1.5§ 83.0 ± 2.5 78.1 ± 1.9 74.1 ± 1.9 
HbA1c (%) 5.40 ± 0.07§ 5.36 ± 0.14 5.43 ± 0.08 5.1 ± 0.03 
Basal metabolic rate (kJ/kg BW) 20.10 ± 0.55§ 18.35 ± 0.69 21.75 ± 0.65* 22.03 ± 0.51 
Basal metabolic rate (kJ/kg FFM) 30.50 ± 0.33 29.35 ± 0.50 31.58 ± 0.42* 30.57 ± 0.39 
GDMGDM-RGDM-SNGT
Age (years) 31.1 ± 0.81 31.0 ± 1.4 31.2 ± 1.0 30.6 ± 1.3 
BMI (kg/m226.4 ± 1.1 29.8 ± 1.8 24.9 ± 0.8* 24.3 ± 0.9 
WHR 0.81 ± 0.01 0.81 ± 0.01 0.80 ± 0.01 0.76 ± 0.02 
Waist (cm) 89.1 ± 2.3§ 96.1 ± 2.5 84.5 ± 2.2* 75.1 ± 2.3 
Triglycerides (mg/dl) 118.2 ± 22.0 136.3 ± 50.9 105.9 ± 14.3 75.2 ± 6.3 
Cholesterol (mg/dl) 210.9 ± 7.6 200.3 ± 14.1 218.0 ± 8.3 198.0 ± 12.4 
HDL cholesterol (mg/dl) 61.4 ± 2.7 54.8 ± 4.7 65.8 ± 3.9* 62.1 ± 2.9 
LDL cholesterol (mg/dl) 126.2 ± 6.5 118.9 ± 10.9 131.2 ± 7.9 120.8 ± 11.0 
Systolic blood pressure (mmHg) 116.7 ± 2.2 123.7 ± 3.9 112.3 ± 2.3* 111.5 ± 2.6 
Diastolic blood pressure (mmHg) 80.0 ± 1.5§ 83.0 ± 2.5 78.1 ± 1.9 74.1 ± 1.9 
HbA1c (%) 5.40 ± 0.07§ 5.36 ± 0.14 5.43 ± 0.08 5.1 ± 0.03 
Basal metabolic rate (kJ/kg BW) 20.10 ± 0.55§ 18.35 ± 0.69 21.75 ± 0.65* 22.03 ± 0.51 
Basal metabolic rate (kJ/kg FFM) 30.50 ± 0.33 29.35 ± 0.50 31.58 ± 0.42* 30.57 ± 0.39 
*

P < 0.05 GDM-R versus GDM-S;

P < 0.05 GDM-R versus NGT;

P < 0.05 GDM-S versus NGT;

§

P < 0.05 GDM versus NGT.

TABLE 2

Metabolic parameters of the total group of women with pGDM (n = 39), the insulin-resistant subgroup (GDM-R), and the insulin-sensitive subgroup (GDM-S) compared with women with NGT 4–6 months after delivery

GDMGDM-RGDM-SNGT
FSIGT     
 Insulin sensitivity index [10−4 min−1 (μU/ml)−14.00 ± 0.35§ 1.92 ± 0.10 5.39 ± 0.36* 6.1 ± 0.5 
 Glucose effectiveness (min−10.022 ± 0.007§ 0.021 ± 0.001 0.023 ± 0.006 0.027 ± 0.001 
 Disposition index (10−2 min−10.112 ± 0.011§ 0.094 ± 0.020 0.124 ± 0.015 0.20 ± 0.03 
 Glucose tolerance index (% min−1)10–20min 1.85 ± 0.13 1.90 ± 0.25 1.79 ± 0.15 2.54 ± 0.29 
 AIRg (pmol l−1)3–10min 38.1 ± 4.7 53.5 ± 9.6 27.4 ± 3.4* 35.3 ± 4.5 
OGTT     
 Fasting glucose (mg/dl) 91.1 ± 1.4§ 93.1 ± 1.9 90.0 ± 1.7 77.1 ± 1.2 
 1 h plasma glucose (mg/dl) 151.3 ± 7.3§ 159.1 ± 10.1 145.1 ± 10.4 102.1 ± 4.4 
 2 h plasma glucose (mg/dl) 119.1 ± 5.8§ 121.5 ± 9.0 117.3 ± 7.9 90.5 ± 3.0 
 OGIS (ml · min−1 · m2423.5 ± 11.5§ 385.4 ± 16.5 454.8 ± 11.4* 502.4 ± 12.6 
 Basal secretion rate (pmol · l−1 · min−122.8 ± 2.4§ 27.6 ± 4.9 18.8 ± 1.6 14.5 ± 1.1 
 Dynamic insulin secretion (nmol/l) 51.7 ± 10.3 73.4 ± 20.0 31.83 ± 2.51* 33.6 ± 2.6 
GDMGDM-RGDM-SNGT
FSIGT     
 Insulin sensitivity index [10−4 min−1 (μU/ml)−14.00 ± 0.35§ 1.92 ± 0.10 5.39 ± 0.36* 6.1 ± 0.5 
 Glucose effectiveness (min−10.022 ± 0.007§ 0.021 ± 0.001 0.023 ± 0.006 0.027 ± 0.001 
 Disposition index (10−2 min−10.112 ± 0.011§ 0.094 ± 0.020 0.124 ± 0.015 0.20 ± 0.03 
 Glucose tolerance index (% min−1)10–20min 1.85 ± 0.13 1.90 ± 0.25 1.79 ± 0.15 2.54 ± 0.29 
 AIRg (pmol l−1)3–10min 38.1 ± 4.7 53.5 ± 9.6 27.4 ± 3.4* 35.3 ± 4.5 
OGTT     
 Fasting glucose (mg/dl) 91.1 ± 1.4§ 93.1 ± 1.9 90.0 ± 1.7 77.1 ± 1.2 
 1 h plasma glucose (mg/dl) 151.3 ± 7.3§ 159.1 ± 10.1 145.1 ± 10.4 102.1 ± 4.4 
 2 h plasma glucose (mg/dl) 119.1 ± 5.8§ 121.5 ± 9.0 117.3 ± 7.9 90.5 ± 3.0 
 OGIS (ml · min−1 · m2423.5 ± 11.5§ 385.4 ± 16.5 454.8 ± 11.4* 502.4 ± 12.6 
 Basal secretion rate (pmol · l−1 · min−122.8 ± 2.4§ 27.6 ± 4.9 18.8 ± 1.6 14.5 ± 1.1 
 Dynamic insulin secretion (nmol/l) 51.7 ± 10.3 73.4 ± 20.0 31.83 ± 2.51* 33.6 ± 2.6 
*

P < 0.05 GDM-R versus GDM-S;

P < 0.05 GDM-R versus NGT;

P < 0.05 GDM-S versus NGT;

§

P < 0.05 GDM versus NGT.

TABLE 3

IMCL-S and IMCL-T: BFM and parameters of the leptin system in the total group of women with prior GDM, in the insulin-resistant subgroup (GDM-R) and the insulin-sensitive subgroup (GDM-S) compared with women with during pregnancy NGT 4–6 months after delivery

GDMGDM-RGDM-SNGT
IMCL-S (% water resonance) 1.70 ± 0.18§ 2.00 ± 0.38 1.51 ± 0.13 1.21 ± 0.08 
IMCL-T (% water resonance) 0.66 ± 0.06§ 0.78 ± 0.09 0.58 ± 0.05* 0.41 ± 0.04 
BFM (kg) 26.4 ± 2.1§ 32.5 ± 3.4 21.3 ± 1.8* 18.1 ± 1.4 
Fasting leptin (nmol/l) 16.7 ± 1.5§ 19.6 ± 2.7 14.3 ± 1.6 9.0 ± 1.3 
Bound leptin (nmol/l) 0.60 ± 0.09§ 0.80 ± 0.22 0.48 ± 0.04 1.07 ± 0.13 
Soluble leptin receptor (nmol/l) 3.76 ± 0.28§ 3.77 ± 0.46 3.75 ± 0.36 5.93 ± 0.61 
Fasting leptin/BFM (nmol · l−1 · kg−10.6 ± 0.03§ 0.62 ± 0.06 0.66 ± 0.05 0.48 ± 0.05 
Bound leptin/BFM (nmol · l−1 · kg−10.028 ± 0.005§ 0.029 ± 0.01 0.026 ± 0.004 0.06 ± 0.008 
Soluble leptin receptor/BFM (nmol · l−1 · kg−10.17 ± 0.02§ 0.14 ± 0.02 0.20 ± 0.03 0.36 ± 0.05 
GDMGDM-RGDM-SNGT
IMCL-S (% water resonance) 1.70 ± 0.18§ 2.00 ± 0.38 1.51 ± 0.13 1.21 ± 0.08 
IMCL-T (% water resonance) 0.66 ± 0.06§ 0.78 ± 0.09 0.58 ± 0.05* 0.41 ± 0.04 
BFM (kg) 26.4 ± 2.1§ 32.5 ± 3.4 21.3 ± 1.8* 18.1 ± 1.4 
Fasting leptin (nmol/l) 16.7 ± 1.5§ 19.6 ± 2.7 14.3 ± 1.6 9.0 ± 1.3 
Bound leptin (nmol/l) 0.60 ± 0.09§ 0.80 ± 0.22 0.48 ± 0.04 1.07 ± 0.13 
Soluble leptin receptor (nmol/l) 3.76 ± 0.28§ 3.77 ± 0.46 3.75 ± 0.36 5.93 ± 0.61 
Fasting leptin/BFM (nmol · l−1 · kg−10.6 ± 0.03§ 0.62 ± 0.06 0.66 ± 0.05 0.48 ± 0.05 
Bound leptin/BFM (nmol · l−1 · kg−10.028 ± 0.005§ 0.029 ± 0.01 0.026 ± 0.004 0.06 ± 0.008 
Soluble leptin receptor/BFM (nmol · l−1 · kg−10.17 ± 0.02§ 0.14 ± 0.02 0.20 ± 0.03 0.36 ± 0.05 
*

P < 0.05 GDM-R versus GDM-S;

P < 0.05 GDM-R versus NGT;

P < 0.05 GDM-S versus NGT;

§

P < 0.05 GDM versus NGT.

TABLE 4

Correlations of IMCL-T with modeling parameters (Spearman correlation coefficient, ANOVA)

SpearmanP values
GDM-R   
 OGTT disposition index (nmol/m3−0.67 0.014 
 FSIGT disposition index −0.62 0.028 
GDM-S   
 OGTT disposition index (nmol/m3−0.007 0.98 
 FSIGT disposition index −0.14 0.56 
SpearmanP values
GDM-R   
 OGTT disposition index (nmol/m3−0.67 0.014 
 FSIGT disposition index −0.62 0.028 
GDM-S   
 OGTT disposition index (nmol/m3−0.007 0.98 
 FSIGT disposition index −0.14 0.56 

These studies were supported by the Austrian Science Fund to A.K.-W. (P14515-MED), M.R. (P13722-MED, P13213-MOB), and the Austrian National Bank to H.S. and M.R. (ÖNB 9127). G.P. and A.T. participated in this study within a cooperative project between ISIB-CNR (formerly LADSEB) and the Department of Internal Medicine III, University of Vienna.

We are indebted to A. Hofer, O.H. Lentner, P. Nowotny, and the laboratory staff of the Division of Endocrinology and Metabolism.

1.
Kjos S, Buchanan T: Gestational diabetes mellitus.
N Engl J Med
341
:
1749
–1756,
1999
2.
Kautzky-Willer A, Prager R, Waldhäusl W, Pacini G, Thomaseth K, Wagner OF, Ulm M, Streli C, Ludvik B: Pronounced insulin resistance and inadequate B-cell secretion in lean gestational diabetes mellitus during and after pregnancy.
Diabetes Care
20
:
1717
–1723,
1997
3.
Ward WK, Johnston CLW, Beard JC, Benedetti TJ, Halter JB, Porte D: Insulin resistance and impaired insulin secretion in subjects with histories of gestational diabetes mellitus.
Diabetes
34
:
861
–869,
1985
4.
Damm P, Kuhl C, Bertelsen A, Molsted-Pedersen L: Predictive factors for the development of diabetes in women with previous gestational diabetes mellitus.
Am J Obstet Gynecol
167
:
607
–616,
1992
5.
Pendergrass M, Fazioni E, De Fronzo R: Non-insulin-dependent diabetes mellitus and gestational diabetes mellitus: same disease, another name?
Diabetes Rev
3
:
566
–583,
1996
6.
Buchanan TA, Xiang A, Kjos S, Lee WP, Trigo E, Nader I, Bergner A, Palmer JP, Peters RK: Gestational diabetes: antepartum characteristics that predict postpartum glucose intolerance and type 2 diabetes in Latino women.
Diabetes
47
:
1302
–1310,
1998
7.
Metzger BE, Cho NH, Roston SM, Radvany R: Prepregnancy weight and antepartum insulin secretion predict glucose tolerance five years after gestational diabetes mellitus.
Diabetes Care
16
:
1598
–1605,
1993
8.
Shulman GI: Cellular mechanisms of insulin resistance.
J Clin Invest
106
:
171
–176,
2000
9.
Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM: Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.
N Engl J Med
346
:
393
–403,
2002
10.
Roden M: Non-invasive studies of glycogen metabolism in human skeletal muscle using nuclear magnetic resonance spectroscopy.
Curr Opin Clin Nutr Metab Care
4
:
261
–266,
2001
11.
Perseghin G, Scifo P, DeCobelli F, Pagliato E, Battezzati A, Arcelloni C, Vanzulli A, Testolin G, Pozza G, DelMaschio A, Luzi L: Intramyocellular triglyceride content is a determinant of in vivo insulin resistance in humans. A 1H-13C nuclear magnetic resonance spectroscopy assessment in offspring of type 2 diabetic parents.
Diabetes
48
:
1600
–1606,
1999
12.
Jacob S, Machann J, Rett K, Brechtel K, Volk A, Renn W, Maerker E, Matthaei S, Schick F, Claussen CD, Häring HU: Association of increased intramyocellular lipid content with insulin resistance in lean nondiabetic offspring of type 2 diabetic subjects.
Diabetes
48
:
1113
–1119,
1999
13.
Storlien LF, Jenks AB, Chisholm DJ, Pascoe WS, Khouri S, Kraegen EW: Influence of dietary fat composition on development of insulin resistance in rats: relationship to muscle triglyceride and w-3 fatty acids in muscle phospholipid.
Diabetes
40
:
280
–289,
1991
14.
Pan DA, Lillioja S, Kriketos AD, Milner MR, Baur LA, Bogardus C, Jenkins AB, Storlien LH: Skeletal muscle triglyceride levels are inversely related to insulin action.
Diabetes
46
:
983
–988,
1997
15.
Simoneau JA, Colberg SR, Thaete FL, Kelley DE: Skeletal muscle glycolytic and oxidative enzyme capacities are determinants of insulin sensitivity and muscle composition in obese women.
FASEB J
9
:
273
–278,
1995
16.
Phillips DIW, Caddy S, Ilic V, Fielding BA, Frayn KN, Borthwick AC, Taylor R: Intramuscular triglyceride and muscle insulin sensitivity: evidence for a relationship in non-diabetic subjects.
Metabolism
45
:
947
–950,
1996
17.
Oakes ND, Cooney GJ, Camilleri S, Chisholm DJ, Kraegen EW: Mechanisms of liver and muscle insulin resistance induced by chronic high-fat feeding.
Diabetes
46
:
1768
–1774,
1997
18.
Szczepaniak LS, Babcock EE, Schick F, Dobbins RL, Garg A, Burns DK, Mc Garry JD, Stein DT: Measurement of intracellular triglyceride stores by 1H spectroscopy: validation in vivo.
Am J Physiol
276
:
E977
–E989,
1999
19.
Boesch C, Slotboom J, Hoppeler H, Kreis R: In vivo determination of intramyocellular lipids in human muscle by means of localized 1H-NMR spectroscopy.
Magn Reson Med
37
:
484
–493,
1997
20.
Kelley DE, Mandarino LJ: Fuel selection in human skeletal muscle in insulin resistance. A reexamination.
Diabetes
49
:
677
–683,
2000
21.
Boden G, Lebed B, Schatz M, Homko C, Lemieux S: Effects of acute changes of plasma free fatty acids on intramyocellular fat content and insulin resistance in healthy subjects.
Diabetes
50
:
1612
–1617,
2001
22.
Krssak M, Petersen K, Dresner A, DiPietro L, Vogel SM, Rothman DL, Roden M, Shulman GI: Intramyocellular lipid concentrations are correlated with insulin sensitivity in humans: a 1H NMR spectroscopy study.
Diabetologia
42
:
113
–116,
1999
23.
Frühbeck G, Salvador J: Relation between leptin and the regulation of glucose metabolism.
Diabetologia
43
:
3
–13,
2000
24.
Lewandowski K, O’Callaghan CJ, Dunlop D, Medley GF, O’Hare P, Brabant G: Free leptin, bound leptin, and soluble leptin receptor in normal and diabetic pregnancies.
J Clin Endocrinol Metab
84
:
300
–306,
1999
25.
Brabant G, Horn R, von zur Mühlen A, Mayr B, Wurster U, Heidenreich F, Schnabel D, Grüters-Kieslich A, Zimmermann-Belsing T, Feldt-Rasmussen U: Free and protein bound leptin are distinct and independently controlled factors in energy regulation.
Diabetologia
43
:
438
–442,
2000
26.
Lammert A, Kiess W, Bottner A, Glasow A, Kratzsch J: Soluble leptin receptor represents the main leptin binding activity in human blood.
Biochem Biophys Res Commun
283
:
982
–988,
2001
27.
American Diabetes Association: Clinical practice recommendations 2001.
Diabetes Care
25 (Suppl. 1)
:
S94
–S96,
2002
28.
Pacini G, Tonolo G, Sambataro M, Maiolo M, Ciccarese M, Brocco E, Avagoro A, Nosadini R: Insulin sensitivity and glucose effectiveness: minimal model analysis of regular and insulin modified FSIGT.
Am J Physiol Endocrinol Metab
37
:
E592
–E599,
1998
29.
Kahn SE, Prigeon RL, McCulloch DSK, Boyko EJ, Bergman RN, Schwartz MW, Neifing JL, Ward WK, Beard JC, Palmer JP, et al: Quantification of the relationship between insulin sensitivity and beta-cell function in human subjects. Evidence for a hyperbolic function.
Diabetes
42
:
1663
–1672,
1993
30.
Thomaseth K, Kautzky-Willer A, Ludvik B, Prager R, Pacini G: Integrated mathematical model to assess B-cell activity during the oral glucose tolerance test.
Am J Physiol
270
:
E522
–E531,
1996
31.
Mari A, Pacini G, Murphy E, Ludvik B, Nolan JJ: A model-based method for assessing insulin sensitivity from the oral glucose tolerance test.
Diabetes Care
24
:
539
–548,
2001
32.
Ockenga J, Biscoff SC, Tillmann HL, Rifai K, Widjaja A, Boker KWH, Manns MP, Brabant G: Elevated bound leptin correlates with energy expenditure in cirrhotics.
Gastroenterology
119
:
1656
–1662,
2000
33.
Krebs M, Krssak M, Nowotny P, Weghuber D, Gruber S, Mlynarik V, Bischof M, Stingl H, Fürnsinn C, Waldhäusl W, Roden M: Free fatty acids inhibit the glucose-stimulated increase of intramuscular glucose-6-phosphate concentration in humans.
J Clin Endocrinol Metab
86
:
2153
–2160,
2001
34.
Malenfant P, Tremblay A, Doucet E, Imbeault P, Simoneau JA, Joanisse DR: Elevated intramyocellular lipid concentration in obese subjects is not reduced after diet and exercise.
Am J Physiol Endocrinol Metab
280
:
E632
–E639,
2001
35.
Goodpaster BH, Thaete FL, Simoneau JA, Kelley DE: Subcutaneous abdominal fat and thigh muscle composition predict insulin sensitivity independently of visceral fat.
Diabetes
46
:
1579
–1585,
1997
36.
Johnson MA, Polgar J, Weightman D, Appleton D: Data of the distribution of fiber types in 36 human muscles. An autopsy study.
J Neurol Sci
18
:
111
–129,
1973
37.
Hickey MS, Weidner MD, Gavigan KE, Zheng D, Tyndall GL, Houmard JA: The insulin action-fiber type relationship in humans is muscle groups specific.
Am J Physiol
269
:
E150
–E154,
1995
38.
Dyck DJ, Peters SJ, Glatz J, Gorski J, Keizer H, Kiens B, Liu S, Richter EA, Spriett LL, van der Vusse GJ, Bonen GA: Functional differences in lipid metabolism in resting skeletal muscle of various fiber types.
Am J Physiol
271
:
E340
–E351,
1997
39.
Hickey MS, Carey JO, Azevedo JL, Houmard JA, Pories WJ, Israel RG, Dohm GL: Skeletal muscle fiber type is related to adiposity and in vitro glucose transport rate in humans.
Am J Physiol
268
:
E453
–E457,
1995
40.
Nyholm B, Qu Z, Kaal A, Pedersen SB, Gravholt CA, Andersen JL, Saltin B, Schmitz O: Evidence of an increased number of type IIb muscle fibers in insulin-resistant first-degree-relatives of patients with NIDDM.
Diabetes
46
:
1822
–1828,
1997
41.
Gaster M, Staehr P, Beck-Nielsen H, Schroder HD, Handberg A: GLUT4 is reduced in slow muscle fibers of type 2 diabetic patients. Is insulin-resistance in type 2 diabetes a slow, type 1 fiber disease?
Diabetes
50
:
1324
–1329,
2001
42.
Waldhäusl W, Roden M: The effects of free fatty acids on glucose transport and phosphorylation in human skeletal muscle.
Curr Opin Endocrinol Diabetes
7
:
211
–216,
2000
43.
Oakes ND, Bell KS, Furler SM, Camilleri S, Saha AK, Ruderman NB, Chisholm DJ, Kraegen EW: Diet-induced muscle insulin resistance in rats is ameliorated by acute dietary lipid withdrawal or a single bout of exercise: parallel relationship between insulin stimulation of glucose uptake and suppression of long-chain fatty acyl-CoA.
Diabetes
46
:
2022
–2028,
1997
44.
Brechtel K, Dahl DB, Machann J, Bachmann OP, Wenzel I, Maier T, Claussen CD, Haring HU, Jacob S, Schick F: Fast elevation of the intramyocellular lipid content in the presence of circulating free fatty acids and hyperinsulinemia: a dynamic 1H-MRS study.
Magn Reson Med
45
:
179
–183,
2001
45.
Ye JM, Doyle PJ, Iglesias MA, Watson DG, Cooney GJ, Kraegen EW: Peroxisome proliferator-activated receptor (PPAR)-alpha activation lowers muscle lipids and improves insulin sensitivity in high-fat-fed rats. Comparison with PPAR-gamma activation.
Diabetes
50
:
411
–417,
2001
46.
Azen SP, Peters RK, Berkowitz K, Kjos S, Xian A, Buchanan TA.TRIPOD (troglitazone: in the prevention of diabetes): a randomized, placebo-controlled trial of troglitazone in women with prior gestational diabetes mellitus.
Control Clin Trials
19
:
217
–231,
1998
47.
Kelley DE, Goodpasture BH: Skeletal muscle triglyceride. An aspect of regional adiposity and insulin resistance.
Diabetes Care
24
:
933
–941,
2001
48.
Kautzky-Willer A, Pacini G, Tura A, Bieglmeyer C, Schneider B, Ludvik B, Prager R, Waldhäusl W: Increased plasma leptin in gestational diabetes.
Diabetologia
44
:
164
–172,
2001
49.
Stock P, Scholl Th, Schluter M, Schroeder Ch: Plasma leptin influences gestational weight gain and postpartum weight retention.
Am J Clin Nutr
8
:
1236
–1240,
1998
50.
McNeely MJ, Boyko EJ, Weigle DS, Shofer JB, Chessler SD, Leonnetti DL, Fujimoto WY: Association between baseline plasma leptin levels and subsequent development of diabetes in Japanese Americans.
Diabetes Care
22
:
65
–70,
1999
51.
Seufert J, Kiefer TJ, Leech CA, Holz GG, Moritz W, Ricordi C, Habener JF: Leptin suppression of insulin secretion and gene expression in human pancreatic islets: implications for the development of adipogenic diabetes mellitus.
J Clin Endocrinol Metab
84
:
670
–676,
1999
52.
Huang L, Wang Z, Li C: Modulation of circulating leptin levels by its soluble receptor.
J Biol Chem
276
:
6343
–6349,
2001

Address correspondence and reprint requests to Michael Roden, MD, Division of Endocrinology and Metabolism, Department of Internal Medicine III, University of Vienna, Währinger Gürtel 18-20, A-1090, Vienna, Austria. E-mail: michael.roden@akh-wien.ac.at.

Received for publication 25 June 2002 and accepted in revised form 16 October 2002.

AIRg 3–10, acute insulin response 3–10 min after glucose ingestion; BFM, body fat mass; BW, body weight; FFM, fat-free mass; GDM, gestational diabetes mellitus; IMCL, intramyocellular lipid content; IMCL-S, IMCL of soleus muscle; IMCL-T, IMCL of tibialis anterior; NGT, normal glucose tolerance; NMRS, nuclear magnetic resonance spectroscopy; OGIS, insulin sensitivity parameter; OGTT, oral glucose tolerance test; pGDM, previous gestational diabetes mellitus; SI, insulin sensitivity index.