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Departments of Medicine (U.S., J.Z., E.R., I.V., J.P., M.L.), Radiology (S.K.), and Clinical Chemistry (K.P.), University of Kuopio, 70210 Kuopio, Finland
Address all correspondence and requests for reprints to: Dr. Markku Laakso, Department of Medicine, University of Kuopio, 70210 Kuopio, Finland. E-mail: markku.laakso{at}kuh.fi.
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Abstract |
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Design: We performed detailed metabolic studies in a large cohort (n = 158) of offspring of patients with type 2 diabetes (T2DM) to determine the association of adiponectin level with glucose and lipid oxidation, energy expenditure, insulin sensitivity, and visceral obesity by applying the euglycemic clamp technique and indirect calorimetry.
Results: The adiponectin level was lower in offspring of T2DM patients than in control subjects. When the data were analyzed by adiponectin tertiles, an elevated adiponectin level was associated with high total, oxidative, and nonoxidative glucose disposal and high energy expenditure during hyperinsulinemia; low levels of free fatty acids and low rates of lipid oxidation during hyperinsulinemia; as well as low levels of inflammatory cytokines; and a low amount of intraabdominal fat evaluated by computed tomography. No association of single nucleotide polymorphism 45 or single nucleotide polymorphism 276 with adiponectin level was found.
Conclusions: We conclude that adiponectin has multiple effects on glucose, lipid and free fatty acid metabolism, and cytokines in offspring of T2DM subjects.
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Introduction |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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, IL-6, plasminogen activator inhibitor-1, leptin, and resistin. Hypoadiponectinemia is also associated with insulin resistance, type 2 diabetes (T2DM), and atherosclerosis (1, 2, 3, 4). An increase in adiponectin concentration is observed with weight loss (5).
Based on recent animal studies, adiponectin enhances insulin sensitivity in both skeletal muscle and liver. The globular domain of adiponectin ameliorated hyperglycemia and hyperinsulinemia in both insulin-resistant lipoatropic mice and obese mice by decreasing the triglyceride content in skeletal muscle and liver (6). A single injection of full-length recombinant adiponectin in mice triggered a transient decrease in the basal glucose level and suppressed gluconeogenesis in isolated hepatocytes (7). Furthermore, peroxisomal proliferator-activated receptor-
agonist rosiglitazone has been shown to increase both the adiponectin mRNA level in adipose tissue and its plasma concentration, suggesting that adiponectin mediates the insulin-sensitizing effect of rosiglitazone (8, 9).
Results concerning the role of adiponectin in the control of body weight and energy expenditure have been somewhat conflicting. Adiponectin knockout mice do not have changes in body weight or fat content compared with wild-type mice (10, 11), whereas a continuous administration of adiponectin (12) or its globular domain (13) has resulted in significant weight loss in mice without affecting food intake. In a single human study, no correlation between adiponectin plasma level and 24-h energy expenditure was observed (14).
Variants in the adiponectin gene have been suggested to contribute to the risk of T2DM and circulating levels of adiponectin. In fact, genome-wide scans have mapped a susceptibility locus of the metabolic syndrome and T2DM to chromosome 3q27, where the adiponectin gene is located (15, 16). Subsequently, several single nucleotide polymorphisms (SNPs) and haplotypes of the adiponectin gene have been associated with insulin resistance, T2DM, and hypoadiponectinemia (17, 18, 19, 20, 21). Reduced circulating adiponectin levels have also been observed in insulin-resistant, first-degree relatives of T2DM patients (22).
There have been no previous studies of the offspring of type 2 diabetic patients with respect to the association of adiponectin with oxidative and nonoxidative glucose metabolism, lipid oxidation, energy expenditure, and cytokine levels during hyperinsulinemia. Therefore, we investigated the association of adiponectin level with these variables, insulin sensitivity, and adiposity in 158 nondiabetic offspring of patients with T2DM. We also assessed the effects of two single nucleotide polymorphisms (SNP 45 and SNP 276) on adiponectin level and different anthropometric and metabolic variables.
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Subjects and Methods |
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One hundred fifty-eight offspring of patients with T2DM and 20 healthy normoglycemic control subjects with no family history of T2DM were included in the study. The probands were randomly selected among the T2DM patients living in the Kuopio University Hospital region. The spouses of patients with T2DM had normal glucose tolerance. The exclusion criteria for the selection of the offspring were 1) diabetes mellitus or any other disease that could potentially disturb carbohydrate metabolism, 2) diabetes mellitus in both parents, 3) pregnancy, and 4) age less than 25 yr or more than 50 yr. The ethics committees of University of Kuopio and Kuopio University Hospital approved the study protocol. All study subjects gave informed consent.
Study design
The studies were conducted in the metabolic ward of Department of Medicine, Kuopio University Hospital, on three different occasions, 1–2 months apart. On the first day, the subjects were interviewed about their medical history, tobacco and alcohol consumption, and exercise habits. Blood pressure was measured with a mercury sphygmomanometer while the patient was in a sitting position after a 5-min rest. Height and weight were measured to the nearest 0.5 cm and 0.1 kg, respectively. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Waist (at the midpoint between the lateral iliac crest and the lowest rib) and hip circumference (at the level of the trochanter major) were measured to the nearest 0,5 cm. Blood samples were drawn for measurements of plasma glucose, insulin, C peptide, and serum lipids after a 12-h fast, followed by an oral glucose tolerance test (OGTT). On the second occasion, bioelectric impedance measurement and indirect calorimetry were performed after a 12-h fast, followed by an iv glucose tolerance test (IVGTT) and a hyperinsulinemic euglycemic clamp, respectively. Indirect calorimetry was reperformed during the last 30 min of the euglycemic clamp. On the third occasion, a computed tomography scan for the evaluation of the abdominal fat volume and distribution was performed.
Oral glucose test
In a 2-h OGTT (75 g glucose), blood samples for plasma glucose and insulin determinations were drawn at 0, 30, 60, 90, and 120 min. Those with normal or impaired (IGT) glucose tolerance according to the World Health Organization criteria (23) were included in the study.
IVGTT
An IVGTT was performed to determine the first phase insulin secretion capacity (24). After an overnight fast, an iv catheter was placed into the left antecupital vein for the infusion of glucose. Another cannula for blood sampling was inserted into a vein in the dorsum of the right hand, which was placed in a heated (40 C) box for arterialization of venous blood. After baseline blood collection, a bolus of glucose (300 mg/kg in a 50% solution) was given within 30 sec into the antecupital vein to acutely raise the blood glucose level. Samples for the measurement of blood glucose and plasma insulin were drawn at –5, 0, 2, 4, 6, 8, and 10 min.
Euglycemic clamp and indirect calorimetry
The degree of insulin sensitivity was evaluated with the euglycemic hyperinsulinemic clamp technique (25). After an IVGTT, a priming dose of insulin (100 IU/ml; Actrapid, Novo Nordisk, Gentofte, Denmark) was administered during the initial 10 min to acutely raise plasma insulin to the desired level, where it was maintained by a continuous infusion rate of 40 mU/min·m2 body surface area. Blood glucose was clamped at 5.0 mmol/liter for the next 120 min by infusing 20% glucose at varying rates according to blood glucose measurements performed at 5-min intervals. The mean amount of glucose given was calculated for each 20-min interval, and the mean value for the last 20-min interval was used to define the rates of whole body glucose uptake (WBGU). Samples for plasma lactate, insulin, and serum free fatty acid (FFA) measurements were drawn at 0 and 120 min.
Indirect calorimetry was performed with a computerized flow-through canopy gas analyzer system (DELTATRAC, TM Datex, Helsinki, Finland). Gas exchange was measured for 30 min in the fasting state and during the last 30 min of the euglycemic clamp. The values obtained during the first 10 min were discarded, and the mean value of the remaining 20-min data was used for calculations of glucose and lipid oxidation. Protein oxidation was calculated on the basis of the urinary nonprotein nitrogen excretion rate (26). The fraction of carbohydrate nonoxidation during the euglycemic clamp was estimated by subtracting the carbohydrate oxidation rate from the glucose infusion rate.
Body composition and fat distribution
Body composition was determined by bioelectrical impedance (RJL Systems, Detroit, MI) while the subject was in the supine position after a 12-h fast. Abdominal fat distribution was evaluated by computed tomography (Volume Zoom, Siemens, Erlanger, Germany) at the level of fourth lumbar vertebra. Subcutaneous and intraabdominal fat (IAF) areas were calculated as previously described (27).
Assays and calculations
Blood and plasma glucose levels were measured by the glucose oxidase method (Glucose & Lactate Analyzer 2300 Stat Plus, YSI, Inc., Yellow Springs, OH). Plasma insulin and C peptide were determined by RIA (Phadeseph Insulin RIA 100, Pharmacia Biotech, Uppsala, Sweden). Serum lipid and lipoprotein concentrations were determined from fresh serum samples drawn after a 12-h overnight fast. Cholesterol and triglyceride levels from whole serum and lipoprotein fractions were assayed by automated enzymatic methods (Roche, Mannheim, Germany). Serum FFAs were determined using an enzymatic method from Wako Chemicals GmbH (Neuss, Germany). TNF-, IL-1ß, IL-1 receptor antagonist, IL-6, IL-8, and IL-10 were measured by solid phase ELISA (Quantikine, R&D Systems, Inc., Minneapolis, MN; and IL-8 UltraSensitive ELISA, BioSource International, Camarillo, CA). C-Reactive protein (CRP) was determined by an Immulite 2000 High Sensitivity CRP assay (Diagnostic Products Corp., Los Angeles, CA), and adiponectin was determined using the human adiponectin ELISA kit (B-Bridge International, Inc., San Jose, CA). Nonprotein urinary nitrogen was measured using the automated Kjeldahl method (28).
DNA analysis
The SNaPshot ddNTP Primer Extension Kit technique was used to genotype SNP 45 T/G and SNP 276 G/T of the adiponectin gene. Forward (5'-GGCTCAGGATGCTGTTGCTGG-3') and reverse (5'-GCT TTG CTT TCT CCC TGT GTC T-3') primers were used to amplify a 328-bp DNA fragment. The following cycling conditions were used for the PCR: 94 C for 4 min and 35 cycles of 94 C for 30 sec, 57 C for 30 sec, 72 C for 30 sec, and 72 C for 4 min. The PCR product was purified with 1 U shrimp alkaline phosphatase and 2 U exonuclease I, incubated at 37 C for 60 min and at 75 C for 15 min.
Primers used to determine the genotypes were 5'-CTGCTATTAGCTCTGCCCGG-3' for the SNP 45 T/G polymorphism and 5'-ACCTCCTACACTGATATAAACTAT-3' for the SNP 276 G/T polymorphism. The SNaPshot reaction was performed with a mixture containing 3.75 µl Tris-HCl, 1.25 µl SNaPshot Multiplex Ready Reaction Mix, Applied Biosystems, Foster City, CA), 0.15 µl primer for SNP 45, 0.075 µl primer for SNP 276, and 0.775 µl distilled H2O. The mixture was incubated for 10 sec at 94 C and for 45 cycles of 96 C for 10 sec, 50 C for 5 sec, and 60 C for 30 sec. The reaction mixture was purified with 1 U shrimp alkaline phosphatase at 37 C for 60 min and 75 C for 15 min. Before loading onto the ABI PRISM 3100 Genetic Analyzer (Applied Biosystems), 9 µl formamide and 0.25 µl GeneScan, 120 LIZ size standard (Applied Biosystems) were added to 0.5 µl of the reaction mixture, and samples were heated in 95C for 5 min.
Statistical analysis
All data analyses were performed with the SPSS 11.0 for Windows program (SPSS, Inc., Chicago, IL). The results for continuous variables are given as the mean ± SD. Variables with skewed distribution (insulin, triglycerides, and cytokines) were logarithmically transformed for statistical analyses. The differences among the three groups were assessed by one-way ANOVA for continuous variables and by 
2 test for categorical variables. Linear mixed model analysis was applied to adjust for confounding factors. For mixed effect models we included the pedigree (coded as a family number) as a random factor, the adiponectin tertiles and gender as fixed factors, and waist, BMI, or IAF as covariates. If the P value for the covariance parameter for the random effect was greater than 0.1, pedigree membership was excluded from the model, and the analysis of covariance was used for additional adjustment. Correlation between continuous variables was tested using linear regression analysis. The incremental insulin areas under the curve were calculated using the trapezoidal method. Haplotype frequencies were estimated using EH software (available from ftp://linkage.rockefeller.edu/software/eh/). Linkage disequilibrium between the two SNPs was calculated with the two-locus linkage disequilibrium calculator (available from http://web1.iop.kcl.ac.uk/IoP/Departments/PsychMed/GEpiBSt/software.shtml).
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Results |
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Basic characteristics of the study population are shown in Table 1
. Twenty-four (15.2%) of the offspring of T2DM patients had IGT. They were overweight and had higher blood pressure and higher fasting and 2-h plasma insulin levels than control subjects. There were no significant differences in gender or age distribution between the groups. There was a tendency toward lower adiponectin concentrations in the offspring of diabetic probands (by ANOVA, P = 0.053). However, the difference between normoglycemic offspring (9.53 ± 4.11 µg/ml) and control subjects (11.42 ± 5.11 µg/ml) was not statistically significant (P = 0.064), and the difference between subjects with IGT (8.43 ± 2.63 µg/ml) and control subjects (P = 0.017) was no longer significant if adjusted for gender and BMI (P = 0.059) or waist (P = 0.162).
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). Women had higher adiponectin level than men (10.65 ± 4.19 and 7.76 ± 2.89 µg/ml, respectively; P < 0.001), but age had no effect on adiponectin concentration. BMI, fasting plasma glucose, fasting plasma insulin, or 2-h plasma insulin in an OGTT, and triglycerides were inversely and high-density lipoprotein (HDL) cholesterol was positively associated with adiponectin level. Except for BMI, the differences remained statistically significant after adjustment for gender and waist circumference, and except for fasting glucose, the differences also remained significant after adjustment for gender and visceral fat, suggesting that the effect of adiponectin on lipid and insulin metabolism was independent of visceral obesity.
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There were no significant differences in fasting energy expenditure, fasting glucose, or lipid oxidation among the adiponectin tertiles (data not shown). However, during the hyperinsulinemic clamp, the rates of WBGU/lean body mass (LBM) were significantly higher in the highest adiponectin tertile concentration than in the two other tertiles (50.15 ± 16.12, 53.44 ± 15.96, and 64.76 ± 15.91 µmol/kg·min; P < 0.001, adjusted for gender; Fig. 1A). The differences in the rates of WBGU were attributable to both nonoxidative (32.16 ± 14.18, 33.50 ± 13.72, and 41.10 ± 13.43 µmol/kg·min; P = 0.001, adjusted for gender) and oxidative (18.51 ± 5.75, 20.55 ± 4.64, and 23.70 ± 4.70 µmol/kg·min; P < 0.001, adjusted for gender) glucose disposal. Similarly, the insulin response in an IVGTT was lowest in the group with the highest adiponectin concentration, reflecting better insulin sensitivity (2188.9 ± 1929.1, 2401.8 ± 1269.0, and 1447.0 ± 831.9 pmol/liter·min; P = 0.003, adjusted for gender; P = 0.016, adjusted for gender and BMI; Fig. 1B). The amount of IAF was inversely associated with adiponectin concentration (122.9 ± 55.3, 120.7 ± 69.7, and 71.2 ± 42.4 cm2; P < 0.001; P = 0.001, adjusted for gender; Fig. 1C). No significant differences in the amount of sc fat between the adiponectin tertiles was found (250.9 ± 108.8, 263.5 ± 124.7, and 244.1 ± 130.5 cm2; P = 0.456).
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). Similarly, the change in energy expenditure from fasting to the hyperinsulinemic state during the clamp increased among the adiponectin tertiles (0.55 ± 1.52, 0.77 ± 1.19, and 1.40 ± 1.24 mg/kg·min; P = 0.005; P = 0.019, adjusted for gender and waist). The respiratory quotient increased with the adiponectin tertiles (0.89 ± 0.05, 0.91 ± 0.04, and 0.93 ± 0.03; P < 0.001 and P = 0.049, adjusted for gender and waist), suggesting differences in fuel preference. There was also a trend for lower lipid oxidation during the clamp with increasing adiponectin tertiles (0.47 ± 0.40, 0.43 ± 0.31, and 0.31 ± 0.28 mg/kg·min; P = 0.041; Fig. 2B), but the differences were not statistically significant after adjustment for gender and waist.
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), but after the adjustment for gender and waist circumference, the difference lost its statistical significance (P = 0.148). Adiponectin, insulin sensitivity, and intraabdominal fat
The relationship between adiponectin level, and insulin sensitivity and visceral obesity was also studied using linear regression analysis (Table 3). Adiponectin correlated with the rates of WBGU (ß = 0.366; P < 0.001) and inversely with intraabdominal fat (ß = –0.408; P < 0.001). After inclusion of age, gender, and the rates of WBGU as independent variables into the regression model, adiponectin no longer had an association with IAF (ß = –0.117; P = 0.136), but the association with the rates of WBGU remained statistically significant even after the inclusion of age, gender, and IAF in the model (ß = 0.229; P = 0.007).
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We also determined correlations of adiponectin level with central inflammatory cytokines (IL-6, CRP, TNF-, IL-1ß, IL receptor antagonist, and IL-8). Only the correlations with IL-6 (r = –0.231; P = 0.009), CRP (r = –0.180; P = 0.042), and IL-1ß (r = –0.246; P = 0.005) were statistically significant.
Adiponectin level and adiponectin genotypes
The genotype frequencies of SNP 45 T/G and SNP 276 G/T were as follows: 142 (91.0%) TT and 14 (9%) TG for SNP 45, and 70 (44.9%) GG, 67 (42.9%) GT, and 19 (12.2%) TT for SNP 276. Genotype distributions were in Hardy-Weinberg equilibrium at both loci, and SNPs were in linkage disequilibrium with each other (D' = –0.997). The adiponectin level did not differ between the genotypes of SNP 45 (TT, 9.31 ± 3.73; TG, 10.51 ± 5.84 µg/ml) or SNP 276 (GG, 9.50 ± 4.03; GT, 9.35 ± 4.14; TT, 9.34 ± 3.10 µg/ml). Genotype combinations of SNP 45 and SNP 276 were formed as reported by Menzaghi et al. (17). Estimated haplotype frequencies of genotype combinations were 0.617 for TG, 0.340 for TT, 0.042 for GG, and 0.001 for GT. There were no statistically significant differences in clinical or laboratory characteristics according to either SNP 45/SNP 276 genotypes (data not shown) or their haplotypes (Table 4). Furthermore, no significant associations between adiponectin levels and either SNP 45/SNP 276 genotypes or their haplotypes were found.
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Offspring of type 2 diabetic patients are insulin resistant and at high risk of developing T2DM. Therefore, studies of adiponectin and its association with metabolic parameters are especially interesting among these individuals. However, there are only two previous studies of adiponectin in the first-degree relatives of patients with T2DM. Lihn et al. (22) found reduced expression of adiponectin in adipose tissue of first-degree relatives of T2DM (n = 22) compared with controls (n = 13), whereas serum adiponectin levels were similar in the two groups. In a study by Pellme et al. (29), the first-degree relatives (n = 45) had lower adiponectin levels than the control group (n = 40), and the difference remained significant after adjustment for obesity. These studies included substantially fewer subjects than our study, and in neither of these two studies was oxidative or nonoxidative glucose disposal determined nor was energy expenditure or cytokines measured in the fasting state or during hyperinsulinemia. Also in our study, the offspring of T2DM patients had lower adiponectin levels than controls, although no statistically significant differences were found between controls and offspring with normal glucose tolerance.
Adiponectin has a profound effect on glucose and lipid metabolism (30, 31). One mechanism by which adiponectin mediates its effect is through activating 5'-AMP-activated protein kinase (AMPK), which plays a central role in the regulation of cellular energy metabolism (32). In skeletal muscle, AMPK activation has been shown to increase glucose transporter-4 translocation and glucose uptake (33). Our results, indicating that both oxidative and nonoxidative glucose metabolism, were similarly improved in subjects with high adiponectin levels are in agreement with these findings. AMPK activates hepatic FFA oxidation and ketogenesis, inhibits triglyceride synthesis, and stimulates skeletal muscle FFA oxidation and glucose uptake (34). In accordance with these mechanisms, we found that total triglyceride level and fasting glucose were negatively associated with adiponectin concentration, in agreement with an inhibitory effect of adiponectin on hepatic lipid metabolism and gluconeogenesis. In contrast, the HDL cholesterol level was positively associated with the adiponectin level. Furthermore, the adiponectin level was inversely related to FFA levels and lipid oxidation during hyperinsulinemia. These abnormalities contribute to the insulin resistance in glucose metabolism observed in subjects with low adiponectin levels (35).
Limited data are available on the association between adiponectin and energy expenditure. Stefan et al. (14) studied 93 nondiabetic subjects and found no correlation between adiponectin and 24-h energy expenditure, assessed by a respiratory chamber or the 24-h respiratory quotient. Similarly, we did not find differences in fasting energy expenditure or in fasting fuel partitioning among the adiponectin tertiles. During hyperinsulinemia, energy expenditure per unit of LBM increased with increasing adiponectin concentration in our study. Data from animal studies support the idea that adiponectin affects the metabolic rate, because adiponectin has been shown to attenuate weight gain (6, 13). Furthermore, administration of adiponectin to agouti yellow obese mice increased uncoupling protein-1 mRNA expression and sympathetic nerve activity in brown adipose tissue, accompanied by attenuated weight gain, reduced visceral fat, and increase in rectal temperature (12).
Several single nucleotide polymorphisms in the adiponectin gene (45T
G, 276GT, and 517TC) have been associated with low adiponectin levels, obesity, and T2DM, although there is some inconsistency among these results. The 45T allele has been associated with insulin resistance in Italian subjects (17), whereas the 45G allele was associated with increased T2DM risk in Japanese subjects (18). The association of the G allele of SNP 276 with the risk of T2DM and lower adiponectin levels has been reported in two studies (18, 36). In contrast, subjects with the T allele of SNP 276 have been shown to be more insulin resistant (37) or have a significantly increased risk of T2DM than subjects with the GG genotype among carriers of the Ala allele of the peroxisome proliferator-activated receptor-2 gene (38). We observed no significant difference in adiponectin levels between offspring of T2DM patients and control subjects after adjustment for gender and obesity, or between SNPs of the adiponectin gene (SNP 45 and SNP 276). The differences between our results and previous findings could be attributable to the possibility that the SNP 276 is in linkage disequilibrium with some as yet unknown polymorphisms that affect plasma adiponectin levels and contribute to the risk of diabetes. Furthermore, our negative findings may be due to the small sample size, and therefore, the results of genetic analyses should be considered with caution.
In our study, the adiponectin level had quite a low inverse correlation with CRP and IL-6. Both inflammation markers are also produced in adipocytes and have previously been associated with obesity and insulin resistance (31). No correlation was observed between adiponectin and TNF-, although this cytokine also increases with obesity, and in vitro findings suggest interregulation of adiponectin and TNF- (8, 11). Recently, TNF- mRNA and plasma levels were found to correlate with plasma adiponectin in HIV-associated lipodystrophy syndrome patients, and in vitro TNF- inhibited human adipose tissue adiponectin mRNA by 80% (39). In another human study, the correlation between plasma adiponectin and TNF- was significant in obese, but not lean, subjects (40). Therefore, it is possible that TNF- and adiponectin interact at least locally in adipose tissue, although no correlation between them was found in our study.
Our study not only confirms the association of the plasma adiponectin level with insulin sensitivity and IAF, but also demonstrates for the first time in humans the association of adiponectin with oxidative and nonoxidative glucose metabolism and energy expenditure during hyperinsulinemia. Our data suggest that hypoadiponectinemia is a sign of adipose tissue insulin resistance and that it is a promising single marker for the metabolic syndrome.
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Footnotes |
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First Published Online April 26, 2005
Abbreviations: AMPK, 5'-AMP-activated protein kinase; BMI, body mass index; CRP, C-reactive protein; FFA, free fatty acid; HDL, high-density lipoprotein; IAF, intraabdominal fat; IGT, impaired glucose tolerance; IVGTT, iv glucose tolerance test; LBM, lean body mass; OGTT, oral glucose tolerance test; SNP, single nucleotide polymorphism; T2DM, type 2 diabetes; WBGU, whole body glucose uptake.
Received November 23, 2004.
Accepted April 13, 2005.
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References |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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ligands increase expression and plasma concentrations of adiponectin, an adipose-derived protein. Diabetes 50:2094–2099 agonists: a potential mechanism of insulin sensitization. Endocrinology 143:998–1007, IL-6, and IL-8 in HALS: implications for reduced adiponectin expression and plasma levels. Am J Physiol 285:E1072–E1080
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, oxidative glucose disposal; 
, nonoxidative glucose disposal; A), first-phase insulin secretion (B), and intraabdominal fat mass (C) according to the adiponectin tertiles (I, lowest; II, middle; III, highest tertile). P values are unadjusted. A, P < 0.001, differences in the rates of WBGU and nonoxidative glucose disposal; P = 0.003, difference in oxidative glucose disposal.