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Journal of Clinical Endocrinology & Metabolism , doi:10.1210/jc.2005-1172
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The Journal of Clinical Endocrinology & Metabolism Vol. 91, No. 2 702-708
Copyright © 2006 by The Endocrine Society

Genetic and Nongenetic Determinants of Skeletal Muscle Glucose Transporter 4 Messenger Ribonucleic Acid Levels and Insulin Action in Twins

Heidi Storgaard, Pernille Poulsen, Charlotte Ling, Leif Groop and Allan A. Vaag

Steno Diabetes Center (H.S., A.A.V.), 2820 Gentofte, Denmark; Diabetes Research Center, Department of Endocrinology, Odense University Hospital (P.P.), 5000 Odense, Denmark; and Department of Endocrinology, Lund University, Wallenberg Laboratory, University Hospital MAS (C.L., L.G.), S-20502 Malmo, Sweden

Address all correspondence and requests for reprints to: Dr. Heidi Storgaard, Steno Diabetes Center, Niels Steensens Vej 2, 2820 Gentofte, Denmark. E-mail: hstorgaard{at}dadlnet.dk.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Context: Insulin-stimulated glucose uptake in skeletal muscle is mediated through translocation of the insulin-sensitive glucose transporter 4 (GLUT4)-containing vesicles to the plasma membrane. Thus, skeletal muscle GLUT4 content plays an important role in whole-body insulin sensitivity.

Objectives: The objectives of this study were 1) to examine the relative impact of genetic vs. environmental factors on skeletal muscle GLUT4 mRNA expression using biometric modeling, and 2) to identify factors influencing the expression of GLUT4 and insulin-stimulated whole-body metabolism.

Design: We measured GLUT4 mRNA expression in biopsies from young and elderly monozygotic (MZ) and dizygotic (DZ) twins before and during a 2-h hyperinsulinemic euglycemic clamp including 3-3H-tritiated glucose and indirect calorimetry.

Participants: A random sample of young (22–31 yr; n = 89) and elderly (57–66 yr; n = 69) same sex MZ and DZ twin pairs identified through the Danish Twin Register were studied.

Results: We found a major genetic component in the control of basal and insulin-stimulated GLUT4 mRNA expression in young and elderly twins. GLUT4 gene expression increased upon insulin stimulation in both young and elderly twins. Multiple regression analysis revealed that both basal and insulin-stimulated GLUT4 mRNA expressions were positively related to birth weight and total body aerobic capacity and were higher in MZ vs. DZ twins as well as in males vs. females. Both basal and insulin-stimulated expressions of GLUT4 were independently and significantly related to whole-body in vivo insulin action, nonoxidative glucose metabolism, and glucose oxidation.

Conclusion: We show that skeletal muscle GLUT4 gene expression in twins is significantly and independently related to glucose metabolism and is determined by both genetic and nongenetic factors, including zygosity and birth weight.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
SKELETAL MUSCLE IS the major site for insulin-dependent glucose uptake (1). Type 2 diabetic patients are characterized by a marked decrease in insulin-stimulated glucose utilization in muscle mainly due to reduced glucose uptake and storage (2). Insulin stimulates glucose uptake through the insulin signaling cascade by increasing translocation of the insulin-sensitive glucose transporter (GLUT4)-containing vesicles to the plasma membrane (3) and by controlling the transcription of important genes in its target cells (4).

Genetically engineered mice with targeted disruption of the GLUT4 gene in adipocytes (adipocyte GLUT4 knockout) (5), muscle (muscle GLUT4 knockout) (6) or both adipocytes and muscle tissue (7) exhibit fasting hyperglycemia, insulin resistance, and glucose intolerance. However, several studies have demonstrated normal GLUT4 protein (8, 9, 10) and mRNA (10, 11) levels in skeletal muscle from type 2 diabetic patients. By contrast, a recent study showed a reduced fraction of type 1 fibers combined with a reduction in GLUT4 protein expression in type 1 fibers in obese subjects as well as in type 2 diabetic patients compared with healthy lean controls (12). The researchers speculated that the reduced GLUT4 protein content in the more insulin-sensitive type 1 fibers may contribute to the reduced insulin-stimulated glucose uptake in skeletal muscle from type 2 diabetic patients (12). Furthermore, translocation of GLUT4 from intracellular vesicles to the cell membrane has been shown to be both impaired (13, 14) and normal (15) in type 2 diabetic patients.

It is well known that type 2 diabetes is caused by genetic as well as pre- and postnatal environmental factors. The intrauterine environment is generally accepted as an important determinant of the risk of disease in adulthood. Low birth weight, a marker of intrauterine adversity, has been associated with a variety of adult-onset diseases, including type 2 diabetes (16, 17). In one study, insulin resistance in subjects with low birth weight was associated with an impaired regulation of GLUT4 mRNA expression by insulin in muscle and adipose tissue compared with normal birth weight controls (18). Additionally, a recent study demonstrated a reduced basal muscle protein expression of protein kinase C{zeta} (PKC{zeta}), p85{alpha}, p110ß, and GLUT4 in subjects with low birth weight compared with normal birth weight controls (19).

To examine the influence of genetic and environmental factors on the expression of GLUT4 in human skeletal muscle, we studied mRNA expression of the GLUT in muscle biopsies from young and elderly monozygotic (MZ) and dizygotic (DZ) twins before and after a hyperinsulinemic euglycemic clamp. We recently demonstrated the validity of this twin approach/sample to determine factors controlling peroxisome proliferator-activated receptor {gamma} coactivator (PGC)-1{alpha} and PGC-1ß expression in skeletal muscle (20). As an expansion to this approach we analyzed the relative impact of genetic vs. environmental factors on GLUT4 mRNA expression using biometric modeling (21). Furthermore, we used a stepwise multiple regression analysis to test the independent influence of age, sex, zygosity, birth weight, and body composition on basal and insulin-stimulated GLUT4 gene expression. Finally, we examined the effects of basal and insulin-stimulated GLUT4 gene expressions on the whole-body insulin-stimulated glucose disposal rate (Rd), glucose oxidation (GOX), and nonoxidative glucose metabolism (NOGM).


   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Subjects

Subjects were identified through the Danish Twin Register (22). A random sample of young and elderly, same sex, MZ and DZ twin pairs born in Funen County during 1966–1975 (22–31 yr) and 1931–1940 (57–66 yr) with available original midwife records, including birth weight, were initially included in the study. All potential/eligible subjects were contacted and interviewed. Exclusion criteria were the following: either twin from a pair not willing to participate; information of pre- or postmaturity (birth >3 wk or <3 wk from expected time point); known diabetes; serious heart, liver, or kidney disease; use of medication known to influence glucose or lipid metabolism, including oral contraception, which could not be withdrawn; and pregnancy/lactation.

A total of 98 twin pairs (33 younger MZ; 22 younger DZ; 21 elderly MZ; 22 elderly DZ) were enrolled in the study. The clinical examination included an oral glucose tolerance test (OGTT), whereas gene expression was analyzed in skeletal muscle biopsies from 158 twins (young MZ, 27 pairs, one single twin; young DZ, 17 pairs; elderly MZ, 15 pairs, one single twin; elderly DZ, 19 pairs). The clinical characteristics of these subjects are described in Table 1Go. Zygosity was determined by polymorphic genetic markers (23). Among elderly twins, 76.9% had normal glucose tolerance (NGT), 17.4% had impaired glucose tolerance (IGT; n = 12), and 4.3% (n = 3) had type 2 diabetes. A total of 97.8% of the young twins had NGT, and 2.2% (n = 2) had IGT. The present study was approved by the regional ethical committees and was conducted according to the Helsinki Declaration.


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  		TABLE 1. Clinical characteristics of young and elderly twins

 
Clinical examination

The subjects underwent a 2-d clinical examination separated by 1–2 wk. Each twin pair was investigated simultaneously. The subjects were instructed to abstain from strenuous physical activity for 24 h and to fast overnight (10–12 h) before both examination days.

Day 1 included a standard 75-g OGTT. Weight and height were measured, and body mass index [weight (kilograms)/height (meters)2] was calculated. The waist to hip ratio (WHR) was calculated. Body composition, i.e. lean body mass (LBM) and fat mass, was determined by dual-energy x-ray absorptiometry scanning.

On d 2, subjects underwent a 2-h hyperinsulinemic euglycemic clamp, including 3-3H-tritiated glucose. Indirect calorimetry was performed during two (basal and insulin-stimulated) 30-min steady-state periods using a computerized flow-through canopy gas analyzer system (Deltatrac, Datex, Helsinki, Finland). After an equilibrium period of 10 min, the average gas exchange rates recorded over the steady-state periods were used to calculate rates of glucose and lipid oxidation. The methods were previously described in detail (24).

Muscle biopsies

Two muscle biopsies were obtained from each subject, one before and one during the hyperinsulinemic clamp. Biopsies were obtained from the vastus lateralis muscle under local anesthesia (lidocain) using a Bergstrom needle with suction applied. The biopsy specimens were quickly blotted on filter paper and frozen in liquid nitrogen. The biopsies were stored at –80 C until further processed.

Analytical methods

Plasma glucose concentrations during the OGTT and the hyperinsulinemic euglycemic clamp were analyzed by the glucose dehydrogenase oxidation method. Plasma insulin concentrations were measured using a two-site, two-step, time-resolved, immunofluorometric assay (DELFIA, Wallac Oy, Turku, Finland) as previously described (25). Cross-reactivities with proinsulin, C peptide, and des(31,32)-split product in the insulin assay were all less than 0.4%. Intraassay coefficients of variation in the physiological ranges were 3.6–4.3% for plasma insulin. Interassay coefficients of variation were 1.7–3.4% for plasma insulin. Tritiated glucose was measured as described by Hother-Nielsen and Beck-Nielsen (26).

Calculations of basal and insulin-stimulated Rd

Rd was calculated at 10-min intervals during the steady-state periods using Steele’s non-steady-state equations (27). In the calculations, the distribution volume of glucose was assumed to be 200 ml/kg body weight, and the pool fraction was 0.65. NOGM was calculated as Rd minus GOX, as determined by indirect calorimetry. Rd is expressed as milligrams per kilogram LBM per minute and is presented as mean values of the 30-min steady-state periods (24).

Analysis of GLUT4 and PGC-1{alpha} mRNA levels in skeletal muscle

Total RNA was extracted from frozen skeletal muscle biopsies using the Tri-Reagent kit according to the manufacturer’s instructions (Sigma-Aldrich Corp., St. Louis, MO). cDNA was synthesized using SuperScript II ribonuclease H– reverse transcriptase and random hexamer primers (Invitrogen Life Technologies, Inc., Groningen, The Netherlands). GLUT4 mRNA levels were quantified using TaqMan real-time PCR with an ABI 7900 system (Applied Biosystems, Foster City, CA). Gene-specific probes and primer pairs for GLUT4 (Assays-on-Demand, Hs00168966_m1, Applied Biosystems) were used. Each sample was run in duplicate, and the transcript quantity was normalized to the mRNA level of cyclophilin A (4326316E, Applied Biosystems). For each probe/primer set, a standard curve was generated, which was confirmed to increase linearly with increasing amounts of cDNA.

Statistical methods

Differences in GLUT4 gene expression levels between the different groups studied were analyzed using proc mixed (ANOVA) in the SAS system (SAS Institute, Inc., Cary, NC) for Windows, version 9, in which familiarity was taken into account. Correlations were calculated using Spearman correlation coefficients. All P values were two-tailed, and P < 0.05 was considered significant. Statistical calculations were performed using SigmaStat software (SigmaStat 3.0; Aspire Software International, Leesburg, VA).

Multiple regression analyses were performed to test the independent effects of age, sex, zygosity, birth weight, and body composition on basal and insulin-stimulated GLUT4 gene expression and the independent effects of basal and insulin-stimulated GLUT4 gene expression on whole-body insulin-stimulated Rd, GOX, and NOGM. Adjustments were made for sex and age (bimodal variable) in each model. The regression model took into consideration that the observations within a twin pair cannot be assumed to be independent and that the dependency effects are different for MZ and DZ twin pairs. The multiple regression analyses were performed in proc mixed, with a stepwise elimination of insignificant covariables until obtaining the final reduced models, in the SAS system for Windows, version 9. The significance level for variable elimination was set at 0.05.

Intrapair correlations. Intrapair correlations are correlations between differences in two phenotypic variables within a twin pair. Spearman correlation analyses were performed using SigmaStat software (SigmaStat 3.0). MZ twins are genetically identical, and significant intrapair correlations between differences in two phenotypic variables are therefore determined solely by environmental factors. In contrast, significant intrapair correlations between differences in two phenotypic variables in DZ twins may be determined by either environmental or genetic factors. Importantly, the intrapair analysis allows for control of common environmental and maternal factors, with a putative influence on the outcome among both MZ and DZ twins.

Intraclass correlations. Intraclass correlations (the correlation between the two twins in a pair) and confidence intervals were calculated using the MX software package (21). The correlation gives an estimate of the similarity within MZ and DZ pairs, respectively, and is used to calculate classical heritability estimates [h2 = 2(rMZ – rDZ)]. A significant difference (rMZ > rDZ) indicates a genetic component. Statistical comparisons of intraclass correlations were made after transformation using the Fisher z transformation.

Biometric modeling. The total phenotypic variance is the sum of the variance attributable to the effects of both genotype and environmental factors. The etiological models tested included the following contributions to variance: genetic variance due to additive genetic effects (VA) or dominant genetic effects (VD) and environmental variance due to an individual environment not shared with cotwin (VE) or a common environment shared among cotwins (VC). We used the MX software package, a program for linear structural equation modeling, to estimate the variance components and to compare the different models. Biometric modeling was conducted separately in the two age groups. The heritability (h2) is the proportion of total variance explained by additive (a2) and/or dominance (d2) genetic variance. Models including A, D, C, and E are fitted to the data (ACE, ADE, AE, DE, CE, and E). The fit of each model was assessed by maximum likelihood methods and resulted in a {chi}2 goodness of fit index and probability value that tested the agreement between the observed and the predicted statistics. A small goodness of fit {chi}2 value, a high P value, and a low Akaike’s information criterion, which equals the {chi}2 value minus 2 times the degree of freedom, indicate good correspondence and were used in comparisons of each model leading to a best-fitting model.

Data were logarithmically transformed to ensure normal distribution. For some of the variables (i.e. GLUT4 gene expression during insulin stimulation among the young twins), the variances and/or means across twin pairs and/or zygosity were not equal, and therefore did not fulfill the criteria for model fitting. To achieve similar means and variances, we performed double entry of the data and adjusted the degree of freedom accordingly, allowing application of the model-fitting analysis on data for GLUT4 gene expression during insulin stimulation.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
Clinical characteristics (Table 1Go)

The elderly twins had greater total fat mass, trunk/leg fat ratio, WHR, and body mass index compared with the younger twins. The elderly twins had lower total body aerobic capacity (VO2max), insulin-stimulated whole-body Rd, GOX, and NOGM than the younger twins (Table 1Go).

Impact of insulin and age on skeletal muscle GLUT4 mRNA levels

The expression of GLUT4 was increased upon insulin stimulation in both elderly and young twins (Table 2Go). Basal as well as insulin-stimulated GLUT4 mRNA levels were higher among young compared with elderly twins (Table 2Go).


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  		TABLE 2. Skeletal muscle GLUT4 expression among young and elderly MZ and DZ twins

 
Factors influencing the expression of GLUT4 in skeletal muscle

Multiple regression analysis was used to test the independent effect of the following parameters on basal and insulin-stimulated GLUT4 mRNA levels in skeletal muscle: zygosity, age, sex, birth weight, percentage body fat, trunk/leg fat percentage ratio, family history of type 2 diabetes, and VO2max (Table 3Go). Both basal and insulin-stimulated GLUT4 mRNA levels were positively related to birth weight. Furthermore, MZ twins and men had higher basal and insulin-stimulated GLUT4 gene expression than DZ twins and women, respectively. In addition, insulin-stimulated GLUT4 gene expression was positively related to VO2max.


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  		TABLE 3. Factors influencing skeletal muscle GLUT4 mRNA expression and insulin-stimulated Rd, GOX, and NOGM (multiple regression analysis)

 
Factors influencing Rd, GOX, and NOGM

Multiple regression analysis was used to identify factors, including GLUT4 gene expression, that independently influence insulin-stimulated Rd, GOX, and NOGM in skeletal muscle. Independent explanatory variables included in the models were basal and insulin-stimulated GLUT4 mRNA levels in muscle, zygosity, age, sex, birth weight, percentage body fat, trunk/leg fat ratio, family history of type 2 diabetes, and VO2max. Insulin-stimulated Rd was positively related to basal GLUT4 expression and inversely related to trunk/leg fat ratio. Insulin-stimulated GOX was positively related to insulin-stimulated GLUT4 expression and total fat percentage and inversely related to trunk/leg fat percentage ratio. The insulin-stimulated NOGM was positively related to basal GLUT4 expression and VO2max and inversely related to age and trunk/leg fat percentage ratio (Table 3Go).

Heritability of skeletal muscle GLUT4 mRNA levels, intraclass correlations, and biometric modeling

Intraclass correlations were significantly higher in young MZ vs. DZ twins for both basal and insulin-stimulated GLUT4 gene expression (Table 4Go). The same trend was seen among elderly twins; however, statistical significance was not reached for either basal or insulin-stimulated GLUT4 mRNA levels (Table 4Go).


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  		TABLE 4. Intraclass correlations between skeletal muscle GLUT4 mRNA levels in young and elderly MZ and DZ twins

 
When performing biometric modeling, a major genetic component was seen for basal and insulin-stimulated skeletal muscle GLUT4 gene expression in both young (a2basal = 0.69; a2insulin = 0.63) and elderly (a2basal = 0.69; a2insulin = 0.55) twins (Table 5Go).


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  		TABLE 5. Best-fitting models for skeletal muscle mRNA levels fulfilling the criteria for application of biometric modelling in young and elderly twins

 
Impact of birth weight on skeletal muscle GLUT4 mRNA levels, intrapair correlation

We found significant absolute correlations between birth weight and basal GLUT4 gene expression levels in both young (r = 0.36; P = 0.01) and elderly (r = 0.52; P = 0.01) MZ twins, whereas no correlations were found between birth weight and basal GLUT4 gene expression in young or elderly DZ twins. Furthermore, no significant absolute correlations were seen between birth weight and insulin-stimulated GLUT4 gene expression in either age group.

We found no significant intratwin pair correlations between birth weight and basal GLUT4 gene expression in either MZ or DZ twins of any age. However, there were positive intrapair correlations between birth weight and insulin-stimulated GLUT4 gene expression in both young (r = 0.37; P = 0.04) and elderly (r = 0.34; P = 0.04) DZ twins, whereas no significant intrapair correlations were found among young or elderly MZ twins.


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
Our unique study population, consisting of MZ and DZ twins, allowed us to estimate the relative contributions of genetic vs. environmental factors in the control of skeletal muscle GLUT4 mRNA expression. To our knowledge, no previous study has addressed this issue. Using biometric modeling, we found a major genetic component in both basal and insulin-stimulated GLUT4 gene expression levels among young and elderly twins. Using intraclass correlation coefficients, we identified heritability of GLUT4 expression in the young, but not in the elderly, twins. This indicates that biometric modeling may represent a more sensitive tool in differentiating between genetic vs. nongenetic influences on gene expression as well as on other phenotypes compared with intraclass correlations.

We have previously reported that the Gly482Ser polymorphism of the PGC-1{alpha} gene, predisposing to insulin resistance and type 2 diabetes (28), was associated with an age-dependent decline in the expression of the PGC-1 {alpha} gene (20). The GLUT-4 gene is one of the target genes for PGC-1{alpha}. It was therefore not surprising to find that the expression level of PGC-1{alpha} correlated significantly with the expression of GLUT4 in skeletal muscle (20). Accordingly, it is possible that the PGC-1{alpha} Gly482Ser polymorphism may account for some of the genetic influence on muscle GLUT4 expression. Previous studies have failed to document any associations between polymorphisms in the GLUT4 gene and insulin resistance or with type 2 diabetes (29, 30, 31, 32, 33, 34, 35). We have therefore not genotyped the present study population for GLUT4 gene polymorphisms. However, it is likely that polymorphisms other than that of the PGC-1 gene contribute to the genetic control of GLUT4 expression in muscle.

Physical training has been shown to increase GLUT4 mRNA levels in skeletal muscle (36, 37). In the present study, we found that VO2max was positively related to insulin-stimulated GLUT4 mRNA levels. In fact, specific nucleotide sequences of the GLUT4 promoter responsible for exercise training-induced up-regulation of GLUT4 expression have indicated a gene-environment interaction (38, 39).

Basal GLUT4 gene expression was positively related to both insulin-stimulated Rd and NOGM in the present study. We have recently reported heritability estimates for insulin-stimulated glucose uptake and NOGM in the same twin population (24) and found a near-equal contribution of genetic vs. nongenetic factors to the variance of these metabolic parameters. The positive association between GLUT4 expression and glucose uptake and NOGM in the present study suggests that GLUT4 may account for at least some of the genetic variance in glucose uptake and/or NOGM. Furthermore, studies in knockout mice have shown that targeted genetic disruption of GLUT4 selectively in skeletal muscle causes insulin resistance and glucose intolerance (6). Taken together, these data indicate that the genetic influence on skeletal muscle GLUT4 mRNA levels might be of metabolic relevance.

In our study population, insulin infusion during clamp increased skeletal muscle GLUT4 mRNA expression significantly in both young and elderly twins. This is in accordance with a previous study reporting increased skeletal muscle GLUT4 gene expression in response to insulin in both young and elderly singletons (36). By contrast, insulin failed to increase GLUT4 gene expression in insulin-resistant obese subjects (36), type 2 diabetic patients (36, 40, 41), and their insulin-resistant, first-degree relatives (41). These findings suggest that impaired insulin stimulation of GLUT4 gene expression reflects insulin resistance.

We have previously demonstrated that both basal and insulin-stimulated skeletal muscle GLUT4 mRNA levels decrease with increasing age in the present twin population (20). However, when adjusting for potential confounding variables, such as sex, zygosity, fat percentage, and VO2max, we found no independent effect of age on either basal or insulin-stimulated skeletal muscle GLUT4 mRNA levels despite the fact that the elderly twins were more insulin resistant than the younger twins. In accordance, a recent study reported unchanged basal muscle GLUT4 mRNA and protein levels with increasing age in previously untrained 20- to 70-yr-old males and females despite an approximately 8% decline in insulin sensitivity per decade in both men and women (37). Furthermore, another study found similar basal and insulin-stimulated muscle GLUT4 mRNA expression in 25- and 50-yr-old men and women with comparable insulin sensitivities, confirming that age per se has little, if any, effect on muscle GLUT4 expression (36).

Using the multiple regression analysis, we found that birth weight, zygosity, and sex independently influenced both basal and insulin-stimulated GLUT4 mRNA expression in human skeletal muscle. To our knowledge it has not been reported previously that males have higher levels of GLUT4 mRNA than females.

Several studies have provided evidence for an association between low birth weight, as a marker for an adverse intrauterine environment, and the development of metabolic disorders and insulin resistance later in life (16, 17). As mentioned previously, several studies have reported impaired insulin stimulation of GLUT4 gene expression in insulin-resistant subjects (36, 40, 41). In accordance, skeletal muscle GLUT4 gene expression failed to increase during insulin infusion in insulin-resistant LBW subjects (18). In another recent study we found that LBW in young and lean men was associated with reduced muscle protein expression of GLUT4 in addition to reduced expression of other specific proteins of importance for insulin signaling, including PKC{zeta}, and the p85{alpha} and p110ß subunits of phosphotidylinositol 3-kinase. Interestingly, PKC{zeta}, p85{alpha}, and GLUT4 protein levels were also reduced in the offspring of protein-restricted rats (19). The latter finding together with the absence of any family history of diabetes in the young LBW men indicated that the protein expression abnormalities might have a nongenetic origin. However, it cannot be excluded that the association between low weight at birth, on the one hand, and insulin resistance and type 2 diabetes, on the other, may be due to a genotype influencing both weight at birth and risk of type 2 diabetes. Interestingly, the positive intrapair correlations between birth weight and insulin-stimulated GLUT4 gene expression in both young and elderly DZ twins, but not in MZ twins, do to some extent support that the association between birth weight and basal as well as insulin-stimulated GLUT4 gene expression could be explained by genetic factors. However, some caution is warranted, because the significant intrapair correlations in the DZ twins could have a nongenetic origin, and the lack of a similar finding among the MZ twin pairs could be a statistical type 2 error.

Two thirds of MZ twins share the same placenta (i.e. are monochorionic), and they are therefore potentially exposed to a more adverse intrauterine environment than those of dichorionic MZ twins and DZ twins with separate placentas (42). Keeping the thrifty phenotype hypothesis in mind (43), we were therefore surprised to find that zygosity had an independent impact on skeletal muscle GLUT4 mRNA levels, with both young and elderly MZ twins having a significantly higher basal and insulin-stimulated GLUT4 gene expression compared with DZ twins. These findings are to some extent consistent with our previous observation of higher insulin sensitivity among young MZ compared with DZ twins. Elderly MZ twins, however, displayed a lower insulin sensitivity than DZ twins (22), which is why the higher GLUT4 level among elderly MZ twins could be a compensatory mechanism to overcome the detrimental influence of an adverse prenatal environment on the metabolism, a mechanism that seems to fail with increasing age. The interpretation of the zygosity differences is complicated due to the facts that zygosity may also be genetically determined (44), and the detrimental programming effects of the intrauterine environment associated with zygosity status may be different from those associated with low birth weight.

We found that basal skeletal muscle GLUT4 gene expression influenced insulin-stimulated whole-body Rd and NOGM, whereas insulin-stimulated GOX was associated with insulin-stimulated skeletal muscle GLUT4 mRNA levels. A previous study (45) reported a positive correlation between skeletal muscle GLUT4 protein levels and whole-body Rd and NOGM in young, normal, glucose-tolerant subjects, whereas no correlation between GLUT4 protein content and GOX was seen. These observations are consistent with an important role for skeletal muscle GLUT4 protein and mRNA levels in whole body Rd. Additional evidence is provided by studies in genetically engineered mice. Mice in which GLUT4 has been knocked out selectively in muscle show glucose intolerance, insulin resistance, and fasting hyperglycemia (6), whereas overexpression of muscle GLUT4 increases insulin action (46, 47). In contrast, two previous studies reported similar levels of basal GLUT4 protein and mRNA in skeletal muscle of lean and obese control subjects as well as insulin-resistant subjects (i.e. subjects with IGT, type 2 diabetes, obesity, and/or gestational diabetes) (10, 11). The finding of a positive association between basal GLUT4 mRNA content in skeletal muscle, on the one hand, and Rd as well as NOGM, on the other, in subjects with NGT in the present study as opposed to the similar GLUT4 protein levels in insulin-sensitive and insulin-resistant individuals suggests that impaired insulin-stimulated whole body Rd may involve impaired GLUT4 function or translocation (13, 14) rather than decreased GLUT4 gene expression. Although this study provides evidence for important regulatory mechanisms of glucose homeostasis at the level of GLUT-4 mRNA levels (i.e. the transcriptional level), it does not determine the extent to which similar causal or compensatory mechanisms may operate at the GLUT4 protein expression level (i.e. the translational level). Unfortunately, we were unable to determine GLUT4 protein levels due to the lack of sufficient muscle samples. However, three previous studies have measured both protein and mRNA GLUT4 levels in human skeletal muscle (11, 40, 41). In two of the studies, basal skeletal muscle GLUT4 protein and mRNA levels were similar in control subjects and insulin-resistant subjects (type 2 diabetic subjects, their first-degree relatives, and obese subjects) (11, 40), whereas another study found similar GLUT4 protein content in controls and insulin-resistant subjects, but increased basal GLUT4 mRNA levels in diabetic subjects and their relatives (41). Andersen et al. (40) showed that the GLUT4 protein content in basal muscle biopsies correlated positively with the GLUT4 mRNA content (r = 0.60; P < 0.05), indicating that the basal GLUT4 protein level is under pretranslational control (40). During insulin stimulation, GLUT4 mRNA levels were found to increase in controls (40, 41), but not in type 2 diabetic patients (40, 41) or their first-degree relatives (41), whereas GLUT4 protein levels were unaffected by insulin in both diabetics and their relatives (40, 41). However, in control subjects, insulin stimulation had no effect on (41) or even decreased (40) GLUT4 protein expression. The existing data on the relationship between human skeletal muscle GLUT4 protein and mRNA levels during insulin stimulation seem to be contradictory in control subjects; however, both studies (40, 41) provide evidence for a divergent effect of insulin at protein and mRNA levels. Additional studies are needed to establish the regulatory mechanisms responsible for this divergence.

In summary, the study provides evidence for a major genetic component in the control of basal and insulin-stimulated GLUT4 mRNA expression in young and elderly twins. Skeletal muscle GLUT4 mRNA expression increased upon insulin infusion in both young and elderly twins. The muscle GLUT4 expression level was lower in elderly compared with young twins, but this age difference disappeared after correcting for confounding factors, such as sex and body composition. Both basal and insulin-stimulated skeletal muscle GLUT4 mRNA expressions were, in a complicated and not fully understood manner, influenced by the intrauterine environment, as expressed by birth weight and zygosity. The basal and/or insulin-stimulated expression levels of the GLUT4 gene in skeletal muscle were significantly and independently related to whole body in vivo insulin action (i.e. insulin-stimulated Rd), NOGM, and GOX, indicating an important role for gene expression of GLUT4 in skeletal muscle in the control of glucose metabolism.


   Acknowledgments
 
We are most grateful to all who participated in the study. For skillful assistance, we thank bioanalyst Marianne Modest (Steno Diabetes Center).


   Footnotes
 
This work was supported by grants from the European Union, 6.th. FRAMEWORK: EXGENESIS (Contract 005272); the Danish Medical Research Council, the Danish Diabetes Association, and Swegene.

First Published Online November 15, 2005

Abbreviations: DZ, Dizygotic; GLUT4, glucose transporter 4; GOX, glucose oxidation; IGT, impaired glucose tolerance; LBM, lean body mass; MZ, monozygotic; NGT, normal glucose tolerance; NOGM, nonoxidative glucose metabolism; OGTT, oral glucose tolerance test; PGC, peroxisome proliferator-activated receptor {gamma} coactivator; PKC{zeta}, protein kinase C{zeta}; Rd, glucose disposal rate; VO2max, total body aerobic capacity; WHR, waist to hip ratio.

Received May 25, 2005.

Accepted November 7, 2005.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

  1. DeFronzo RA, Jacot E, Jequier E, Maeder E, Wahren J, Felber JP 1981 The effect of insulin on the disposal of intravenous glucose. Results from indirect calorimetry and hepatic and femoral venous catheterization. Diabetes 30:1000–1007[Medline]
  2. Kahn CR 1994 Banting Lecture. Insulin action, diabetogenes, and the cause of type II diabetes. Diabetes 43:1066–1084[Medline]
  3. Marette A, Burdett E, Douen A, Vranic M, Klip A 1992 Insulin induces the translocation of GLUT4 from a unique intracellular organelle to transverse tubules in rat skeletal muscle. Diabetes 41:1562–1569[Abstract]
  4. O’Brien RM, Granner DK 1996 Regulation of gene expression by insulin. Physiol Rev 76:1109–1161[Abstract/Free Full Text]
  5. Abel ED, Peroni O, Kim JK, Kim YB, Boss O, Hadro E, Minnemann T, Shulman GI, Kahn BB 2001 Adipose-selective targeting of the GLUT4 gene impairs insulin action in muscle and liver. Nature 409:729–733[CrossRef][Medline]
  6. Zisman A, Peroni OD, Abel ED, Michael MD, Mauvais-Jarvis F, Lowell BB, Wojtaszewski JF, Hirshman MF, Virkamaki A, Goodyear LJ, Kahn CR, Kahn, BB 2000 Targeted disruption of the glucose transporter 4 selectively in muscle causes insulin resistance and glucose intolerance. Nat Med 6:924–928[CrossRef][Medline]
  7. Kotani K, Peroni OD, Minokoshi Y, Boss O, Kahn BB 2004 GLUT4 glucose transporter deficiency increases hepatic lipid production and peripheral lipid utilization. J Clin Invest; 114:1666–1675[CrossRef][Medline]
  8. Friedman JE, Dohm GL, Elton CW, Rovira A, Chen JJ, Leggett-Frazier N, Atkinson Jr SM, Thomas FT, Long SD, Caro JF 1991 Muscle insulin resistance in uremic humans: glucose transport, glucose transporters, and insulin receptors. Am J Physiol 261:E87–E94
  9. Handberg A, Vaag A, Damsbo P, Beck-Nielsen H, Vinten J 1990 Expression of insulin regulatable glucose transporters in skeletal muscle from type 2 (non-insulin-dependent) diabetic patients. Diabetologia 33:625–627[CrossRef][Medline]
  10. Pedersen O, Bak JF, Andersen PH, Lund S, Moller DE, Flier JS, Kahn BB 1990 Evidence against altered expression of GLUT1 or GLUT4 in skeletal muscle of patients with obesity or NIDDM. Diabetes; 39:865–870[Abstract]
  11. Garvey WT, Maianu L, Hancock JA, Golichowski AM, Baron A 1992 Gene expression of GLUT4 in skeletal muscle from insulin-resistant patients with obesity, IGT, GDM, and NIDDM. Diabetes 41:465–475[Abstract]
  12. Gaster M, Staehr P, Beck-Nielsen H, Schroder HD, Handberg A 2001 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[Abstract/Free Full Text]
  13. Garvey WT, Maianu L, Zhu JH, Brechtel-Hook G, Wallace P, Baron AD 1998 Evidence for defects in the trafficking and translocation of GLUT4 glucose transporters in skeletal muscle as a cause of human insulin resistance. J Clin Invest 101:2377–2386[Medline]
  14. Zierath JR, He L, Guma A, Odegoard WE, Klip A, Wallberg-Henriksson H 1996 Insulin action on glucose transport and plasma membrane GLUT4 content in skeletal muscle from patients with NIDDM. Diabetologia 39:1180–1189[Medline]
  15. Lund S, Vestergaard H, Andersen PH, Schmitz O, Gotzsche LB, Pedersen O 1993 GLUT-4 content in plasma membrane of muscle from patients with non-insulin-dependent diabetes mellitus. Am J Physiol 265:E889–E897
  16. Barker DJ, Eriksson JG, Forsen T, Osmond C 2002 Fetal origins of adult disease: strength of effects and biological basis. Int J Epidemiol 31:1235–1239[Abstract/Free Full Text]
  17. Hales CN, Barker DJ, Clark PM, Cox LJ, Fall C, Osmond C, Winter PD 1991 Fetal and infant growth and impaired glucose tolerance at age 64. Br Med J 303:1019–1022
  18. Jaquet D, Vidal H, Hankard R, Czernichow P, Levy-Marchal C 2001 Impaired regulation of glucose transporter 4 gene expression in insulin resistance associated with in utero undernutrition. J Clin Endocrinol Metab 86:3266–3271[Abstract/Free Full Text]
  19. Ozanne SE, Jensen CB, Tingey KJ, Storgaard H, Madsbad S, Vaag AA 2005 Low birthweight is associated with specific changes in muscle insulin-signalling protein expression. Diabetologia 48:547–552[CrossRef][Medline]
  20. Ling C, Poulsen P, Carlsson E, Ridderstrale M, Almgren P, Wojtaszewski J, Beck-Nielsen H, Groop L, Vaag A 2004 Multiple environmental and genetic factors influence skeletal muscle PGC-1{alpha} and PGC-1ß gene expression in twins. J Clin Invest 114:1518–1526[CrossRef][Medline]
  21. Neal MC, Cardon LR 1992 Data summary. In: Methodology for genetic studies of twins and families. Dordrecht, Boston, London: Kluwer Academic
  22. Poulsen P, Levin K, Beck-Nielsen H, Vaag A 2002 Age-dependent impact of zygosity and birth weight on insulin secretion and insulin action in twins. Diabetologia 45:1649–1657[CrossRef][Medline]
  23. Morling N 2003 Forensic genetics. Ugeskr Laeger 165:922–925[Medline]
  24. Poulsen P, Levin K, Petersen I, Christensen K, Beck-Nielsen H, Vaag A 2005 Heritability of insulin secretion, peripheral and hepatic insulin action, and intracellular glucose partitioning in young and old Danish twins. Diabetes 54:275–283[Abstract/Free Full Text]
  25. Hemmila I, Dakubu S, Mukkala VM, Siitari H, Lovgren T 1984 Europium as a label in time-resolved immunofluorometric assays. Anal Biochem 137:335–343[CrossRef][Medline]
  26. Hother-Nielsen O, Beck-Nielsen H 1990 On the determination of basal glucose production rate in patients with type 2 (non-insulin-dependent) diabetes mellitus using primed-continuous 3-3H-glucose infusion. Diabetologia 33:603–610[CrossRef][Medline]
  27. Steele R 1959 Influences of glucose loading and of injected insulin on hepatic glucose output. Ann NY Acad Sci 82:420–430
  28. Ek J, Andersen G, Urhammer SA, Gaede PH, Drivsholm T, Borch-Johnsen K, Hansen T, Pedersen O 2001 Mutation analysis of peroxisome proliferator-activated receptor-{gamma} coactivator-1 (PGC-1) and relationships of identified amino acid polymorphisms to type II diabetes mellitus. Diabetologia 44:2220–2226[CrossRef][Medline]
  29. Baroni MG, Oelbaum RS, Pozzilli P, Stocks J, Li SR, Fiore V, Galton D J 1992 Polymorphisms at the GLUT1 (HepG2) and GLUT4 (muscle/adipocyte) glucose transporter genes and non-insulin-dependent diabetes mellitus (NIDDM). Hum Genet 88:557–561[Medline]
  30. Buse JB, Yasuda K, Lay TP, Seo TS, Olson AL, Pessin JE, Karam JH, Seino S, Bell GI 1992 Human GLUT4/muscle-fat glucose-transporter gene. Characterization and genetic variation. Diabetes 41:1436–1445[Abstract]
  31. Friedel S, Antwerpen B, Hoch A, Vogel C, Grassl W, Geller F, Hebebrand J, Hinney A 2002 Glucose transporter 4 gene: association studies pertaining to alleles of two polymorphisms in extremely obese children and adolescents and in normal and underweight controls. Ann NY Acad Sci 967:554–557[Medline]
  32. Jun H, Bae HY, Lee BR, Koh KS, Kim YS, Lee KW, Kim H, Yoon J 1999 Pathogenesis of non-insulin-dependent (type II) diabetes mellitus (NIDDM): genetic predisposition and metabolic abnormalities. Adv Drug Deliv Rev 35:157–177[CrossRef][Medline]
  33. Lesage S, Zouali H, Vionnet N, Philippi A, Velho G, Serradas P, Passa P, Demenais F, Froguel P 1997 Genetic analyses of glucose transporter genes in French non-insulin-dependent diabetic families. Diabetes Metab 23:137–142[Medline]
  34. Oelbaum RS 1992 Analysis of three glucose transporter genes in a Caucasian population: no associations with non-insulin-dependent diabetes and obesity. Clin Genet 42:260–266[Medline]
  35. Pontiroli AE, Capra F, Veglia F, Ferrari M, Xiang KS, Bell GI, Baroni MG, Galton DJ, Weaver JU, Hitman GA, Kopelman PG, Mohan V, Viswanathan M 1996 Genetic contribution of polymorphism of the GLUT1 and GLUT4 genes to the susceptibility to type 2 (non-insulin-dependent) diabetes mellitus in different populations. Acta Diabetol 33:193–197[Medline]
  36. Ducluzeau PH, Perretti N, Laville M, Andreelli F, Vega N, Riou JP, Vidal H 2001 Regulation by insulin of gene expression in human skeletal muscle and adipose tissue. Evidence for specific defects in type 2 diabetes. Diabetes 50:1134–1142[Abstract/Free Full Text]
  37. Short KR, Vittone JL, Bigelow ML, Proctor DN, Rizza RA, Coenen-Schimke JM, Nair KS 2003 Impact of aerobic exercise training on age-related changes in insulin sensitivity and muscle oxidative capacity. Diabetes 52:1888–1896[Abstract/Free Full Text]
  38. MacLean PS, Zheng D, Jones JP, Olson AL, Dohm GL 2002 Exercise-induced transcription of the muscle glucose transporter (GLUT 4) gene. Biochem Biophys Res Commun 292:409–414[CrossRef][Medline]
  39. Tsunoda N, Maruyama K, Cooke DW, Lane DM, Ezaki O 2000 Localization of exercise- and denervation-responsive elements in the mouse GLUT4 gene. Biochem Biophys Res Commun 267:744–751[CrossRef][Medline]
  40. Andersen PH, Lund S, Vestergaard H, Junker S, Kahn BB, Pedersen O 1993 Expression of the major insulin regulatable glucose transporter (GLUT4) in skeletal muscle of noninsulin-dependent diabetic patients and healthy subjects before and after insulin infusion. J Clin Endocrinol Metab 77:27–32[Abstract]
  41. Schalin-Jantti C, Yki-Jarvinen H, Koranyi L, Bourey R, Lindstrom J, Nikula-Ijas P, Franssila-Kallunki A, Groop LC 1994 Effect of insulin on GLUT-4 mRNA and protein concentrations in skeletal muscle of patients with NIDDM and their first-degree relatives. Diabetologia 37:401–407[Medline]
  42. Ramos-Arroyo MA, Ulbright TM, Yu PL, Christian JC 1988 Twin study: relationship between birth weight, zygosity, placentation, and pathologic placental changes. Acta Genet Med Gemellol 37:229–238[Medline]
  43. Hales CN, Barker DJ 1992 Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia 35:595–601[CrossRef][Medline]
  44. Busjahn A, Knoblauch H, Faulhaber HD, Aydin A, Uhlmann R, Tuomilehto J, Kaprio J, Jedrusik P, Januszewicz A, Strelau J, Schuster H, Luft FC, Muller-Myhsok B 2000 A region on chromosome 3 is linked to dizygotic twinning. Nat Genet 26:398–399[CrossRef][Medline]
  45. Koranyi LI, Bourey RE, Vuorinen-Markkola H, Koivisto VA, Mueckler M, Permutt MA, Yki-Jarvinen H 1991 Level of skeletal muscle glucose transporter protein correlates with insulin-stimulated whole body glucose disposal in man. Diabetologia 34:763–765[CrossRef][Medline]
  46. Brozinick Jr JT, Yaspelkis III BB, Wilson CM, Grant KE, Gibbs EM, Cushman SW, Ivy JL 1996 Glucose transport and GLUT4 protein distribution in skeletal muscle of GLUT4 transgenic mice. Biochem J 313:133–140
  47. Tsao TS, Burcelin R, Katz EB, Huang L, Charron MJ 1996 Enhanced insulin action due to targeted GLUT4 overexpression exclusively in muscle. Diabetes 45:28–36[Abstract]



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