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Journal of Clinical Endocrinology & Metabolism , doi:10.1210/jc.2004-0058
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The Journal of Clinical Endocrinology & Metabolism Vol. 90, No. 3 1639-1643
Copyright © 2005 by The Endocrine Society

The –913 G/A Glutamine:Fructose-6-Phosphate Aminotransferase Gene Polymorphism Is Associated with Measures of Obesity and Intramyocellular Lipid Content in Nondiabetic Subjects

Cora Weigert, Claus Thamer, Katrin Brodbeck, Alke Guirguis, Fausto Machicao, Jürgen Machann, Fritz Schick, Michael Stumvoll, Andreas Fritsche, Hans U. Häring and Erwin D. Schleicher

Department of Internal Medicine, Division of Endocrinology, Metabolism, and Pathobiochemistry (C.W., C.T., K.B., A.G., F.M., M.S., A.F., H.U.H., E.D.S.), and Section of Experimental Radiology, Department of Diagnostic Radiology (J.M., F.S.), University of Tubingen, D-72076 Tubingen, Germany

Address all correspondence and requests for reprints to: Dr. Erwin D. Schleicher, Department of Internal Medicine, Division of Endocrinology, Metabolism, and Pathobiochemistry, University of Tubingen, Otfried Müller Strasse 10, D-72076 Tubingen, Germany. E-mail: enschlei{at}med.uni-tuebingen.de.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Increases in glutamine:fructose-6-phosphate aminotransferase (GFAT) protein levels directly activate flux through the hexosamine biosynthetic pathway. This pathway has been involved as a fuel sensor in energy metabolism and development of insulin resistance. We screened the 5'-flanking region of the human GFAT gene for polymorphisms and subsequently genotyped 412 nondiabetic, metabolically characterized Caucasians for the two single-nucleotide polymorphisms (SNP) at positions –913 (G/A) and –1412 (C/G) with rare allele frequencies of 42% and 16%, respectively. The –913 G SNP was associated with significantly higher body mass index and percent body fat in men (P = 0.02 and 0.004, respectively), but not in women (P = 0.47 and 0.26, respectively). In the subgroup of individuals (n = 193) who underwent hyperinsulinemic-euglycemic clamp, an association of the –913 G SNP with insulin sensitivity independent of body mass index was not detected. Moreover, the –913 G allele in a group of 71 individuals who had undergone magnetic resonance spectroscopy was associated with higher intramyocellular lipid content (IMCL) in tibialis anterior muscle (4.21 ± 0.31 vs. 3.36 ± 0.35; P = 0.04) independent of percent body fat and maximal aerobic power. The –1412 SNP had no effect on percent body fat, insulin sensitivity, or IMCL. In conclusion, we identified two polymorphisms in the 5'-flanking region of GFAT, of which the –913 SNP seems to alter the risk for obesity and IMCL accumulation in male subjects.


   Introduction
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 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
GLUTAMINE:FRUCTOSE-6-PHOSPHATE aminotransferase (GFAT), the rate-limiting enzyme of the hexosamine biosynthetic pathway (HBP), catalyzes the conversion of fructose-6-phosphate to glucosamine-6-phosphate (GlcN-6-P) with glutamine as amino donor (1). GlcN-6-P is very rapidly further converted and activated to uridine-5'-diphosphate-N-acetylglucosamine (UDP-GlcNAc), serving as an essential substrate for protein glycosylation (2). Marshall and co-workers (3) discovered that increased flux through the HBP caused by ambient high glucose concentrations and insulin results in decreased insulin action on glucose transport in adipocytes. Several subsequent in vivo studies indicate that activation of the HBP by hyperglycemia (4, 5), glucosamine infusions (6, 7), overexpression of GFAT in transgenic mice (8), or elevated plasma free fatty acids (FFA) (9) impaired glucose uptake and glycogen synthesis in skeletal muscle. Recently, evidence has been provided that the flux through the HBP could be linked to the regulation of energy intake and energy expenditure (10). Thus, the HBP functions as one fuel sensor of the organism (4, 11).

Importantly, increased expression of GFAT is directly linked to flux through the HBP. Overexpression of GFAT in transgenic mice (8) and in cell culture models (12, 13) and induction of GFAT expression by saturated fatty acids in myotubes (14) resulted in increased UDP-GlcNAc levels. Although the impact of cellular GFAT protein levels on the regulation of energy metabolism has been clearly demonstrated, data on the transcriptional regulation of GFAT gene expression are limited (14, 15, 16, 17). Conceivably, polymorphisms in the 5'-flanking region of GFAT might affect this regulation and consequently whole body energy metabolism, obesity, and insulin resistance. In this study we identified a –913 (G/A) and a –1412 (C/G) polymorphism and examined their association with measures of obesity and insulin sensitivity.


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

Subjects were recruited from the ongoing Tubingen Family Study for type 2 diabetes (18, 19), where family members of subjects with type 2 diabetes and control subjects without any family history of diabetes were studied. To date, more than 1000 subjects have been included. A total of 412 (248 females and 164 males) nondiabetic subjects, according to WHO criteria, were selected for analyses. A subgroup of 193 subjects (96 females and 97 males) underwent hyperinsulinemic euglycemic clamp. In 71 subjects undergoing hyperinsulinemic euglycemic clamp, data for intramyocellular lipid content (IMCL) were available for analyses. The subjects were unrelated and had tested negative for glutamic acid decarboxylase; their genotypes were unknown at the time of recruitment. The study protocol was approved by the ethics committee of University of Tubingen. Before the study, informed written consent was obtained from all participants.

Genotyping

The –913 G/A and –1412 C/G polymorphisms were identified by direct sequencing. The 5'-flanking region –1492/+80 of human GFAT was amplified by PCR using the following primers: sense, 5'-cagcttctctgaggcaagtgaaaaaaggc-3'; and antisense, 5'-gggtggcgccgacacgactccc-3'. PCR products were sequenced using a dye terminator cycle sequencing reaction kit (ABI PRISM 310, Applied Biosystems, Foster City, CA). Genotyping was performed using the following primers: for position –913: sense, 5'-ttcctgaagaggtagcatctaaacagag-3'; and antisense, 5'-ggtatctttagtcaaatgtggagtaatcagaa-3'; and for position –1412: sense, 5'-cagcttctctgaggcaagtgaaaaaaggc-3'; and antisense, 5'-ctctgtttagatgctacctcttcaggaa-3'. The single-nucleotide polymorphism (SNP) numbering is based on GenBank accession no. NT_033004.2.

Analytical procedures

Blood glucose was determined using a bedside glucose analyzer (glucose oxidase method, YSI, Inc., Yellow Springs, CO). Plasma insulin was determined by microparticle enzyme immunoassay (Abbott Laboratories, Niesbach, Germany). Lean body mass (kilograms) and total body fat (percentage) were determined by bioimpedance analysis (BIA-101, RJL Systems, Detroit, MI) following the guidelines of the user’s manual and the NIH Consensus Conference on Bioelectric Impedance (20).

Oral glucose tolerance test

After a 10-h overnight fast, the subjects ingested a solution containing 75 g dextrose, and venous blood samples were obtained at 0, 30, 60, 90, and 120 min for determination of plasma glucose and plasma insulin. Stages of glucose tolerance were classified according to WHO criteria (21).

Euglycemic hyperinsulinemic clamp

After a 12-h overnight fast at approximately 0700 h, an antecubital vein was cannulated for infusion of insulin and glucose. A dorsal hand vein of the contralateral arm was cannulated and placed under a heating device to permit sampling of arterialized blood. After basal blood was drawn, subjects received a primed insulin infusion at a rate of 1.0 mU/kg·min for 2 h. Blood was drawn every 5 min for determination of blood glucose, and a glucose infusion was adjusted appropriately to maintain the fasting glucose level. An insulin sensitivity index (micromoles per kilogram per minute per picomolar concentration) for systemic glucose uptake was calculated as the mean infusion rate of glucose (micromoles per kilogram per minute) necessary to maintain euglycemia during the last 60 min of the euglycemic hyperinsulinemic clamp divided by the steady state serum insulin concentration.

Determination of IMCL by magnetic resonance spectroscopy

Neutral lipids within the muscle cell (IMCL) and those interlaced between the muscle fibers can be differentiated due to their geometrical arrangement using proton magnetic resonance spectroscopy (22). Localized image-guided proton spectra of the tibialis anterior muscle representing a muscle of mixed type I and II fibers and of the soleus muscle representing a muscle of predominantly type I fibers with high oxidative capacity were acquired on a 1.5-Tesla whole body imager (Magnetom Vision, Siemens, Erlangen, Germany). For volume selection, a single voxel STEAM technique was applied. Measurement parameters were: echo time, 10 msec; repetition time, 2 sec; volume of interest, 11 x 11 x 20 mm3; and 40 acquisitions. IMCL were quantified as previously described (23, 24).

Measurement of maximal aerobic capacity (VO2max)

Subjects underwent a continuous, incremental exercise test to volitional exhaustion on a cycle ergometer. The cycle ergometer test was performed on an electromagnetically braked cycle ergometer (ergometrics 800 S, Ergoline, Bitz, Germany). Oxygen consumption was measured using a spiroergometer (Breese Ex 3.02 A, MedGraphics, St. Paul, MN). Subjects were asked to choose a pedaling rate of 60 rpm and to maintain that rate throughout the test. After a 2-min warm-up period at 0 watts, the test was initiated at an initial power output of 20 watts. Stepwise increments of 40 watts were made every minute until exhaustion. VO2max is expressed as a percentage of the predicted peak VO2 (milliliters per minute) based on sex, age, and body mass index (BMI), as described previously (24). For the purpose of the present analyses, we used this parameter as a measure of physical fitness.

Statistical analysis

All data are given as the mean ± SE unless otherwise stated. The statistical software package JMP (SAS Institute, Inc., Cary, NC) was used for statistical analyses. Nonnormally distributed variables were log-transformed before statistical analysis. Multiple linear regression models were used to calculate the independent effect of an SNP. Statistical significance was set at P < 0.05.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
To search for polymorphisms in the 5'-flanking region of the human GFAT gene, a 1572-bp fragment corresponding to positions –1492/+80 based on GenBank accession no. NT_033004.2 (now replaced by NT_022184) was amplified from genomic DNA from 20 randomly selected nondiabetic subjects and sequenced. Computer analysis revealed the existence of A to G substitution at –913 and G to C substitution at –1412. The SNP database also contains the –913 A/G SNP, but not the –1412 base substitution, and no other SNPs in the 5'-flanking region of the human GFAT gene –1492/+80.

Next, we genotyped a total of 412 nondiabetic, metabolically characterized subjects for the –913G/A and –1412 C/G polymorphisms. In the entire cohort, the allele frequencies for –913 G, –913A, –1412 C, and –1412 G were 42%, 58%, 84%, and 16%, respectively. Both polymorphisms were in Hardy-Weinberg equilibrium (P = 0.98 for –913 G/A; P = 0.36 for –1412 C/G, by {chi}2 test). All –913 GG carriers were homozygous for the –1412 C allele; none of the –913 GA carriers was homozygous for the –1412 G allele. A list of the frequencies and distribution of both SNPs in the entire cohort is shown in Table 1Go.


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  		TABLE 1. Allele frequencies of the –913 and –1412 SNP in the group of the 412 nondiabetic subjects

 
In men who underwent the oral glucose tolerance test, we found a significantly lower BMI in –913 AA carriers (24.1 ± 0.6 kg/m2) compared with –913 GG and GA carriers combined (25.9 ± 0.5 kg/m2; P = 0.02; Table 2Go), whereas the BMIs in the male –913 GG and GA groups were quite similar (26.0 ± 0.9 and 25.9 ± 0.5 kg/m2, respectively). A parallel and more pronounced difference in percent body fat was observed (17.9 ± 0.8% vs. 21.2 ± 0.6%; P = 0.004; Table 2Go). The difference in waist/hip ratio followed the same line. The effect of the –913 polymorphism on percent body fat was independent of age, as tested in a multivariate regression analysis (P = 0.009 for the –913 SNP; Table 2Go). In the female subgroup, the G allele had no effect on body fat content.


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  		TABLE 2. Characteristics of nondiabetic subjects who underwent the oral glucose tolerance test (OGTT; stratified by sex and –913 genotype)

 
Female carriers of the –1412 G allele had a higher BMI and tended to have a higher percent body fat compared with the female –1412 CC subgroup [27.5 ± 0.7 vs. 25.7 ± 0.5 kg/m2 (P = 0.01); 33.3 ± 1.0 vs. 31.4 ± 0.7 kg/m2 (P = 0.08); data not shown]. However, because the –1412 SNP showed no effect on percent body fat, we concentrated our additional investigations on the –913 polymorphism. Not unexpectedly, because the effects of sex on the body fat content of the –913 G allele and –1412 G allele carriers are in opposite directions, we found no combined effect of the two polymorphisms on measures of obesity.

In the subgroup of 193 individuals who underwent the hyperinsulinemic-euglycemic clamp, again, male carriers of the –913 G allele had a higher BMI than the male –913 AA subgroup (25.0 ± 0.6 vs. 23.1 ± 0.7 kg/m2; P = 0.03; Table 3Go). In this group, the –913 SNP had a significant effect on insulin sensitivity (0.100 ± 0.01 in the GG + GA group compared with 0.122 ± 0.01 in the AA group; P = 0.02; Table 3Go). Thus, male carriers of the G allele had a lower insulin sensitivity and a higher BMI. This effect of the –913 SNP seemed to be secondary to the difference in BMI (Table 3Go).


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  		TABLE 3. Characteristics of nondiabetic subjects who underwent the hyperinsulinemic-euglycemic clamp (stratified by sex and –913 genotype)

 
Because the hexosamine pathway was recently identified as a biochemical link between energy intake and energy expenditure, thereby decreasing the expression of a cluster of genes involved in skeletal muscle fatty acid oxidation and oxidative phosphorylation, we studied the effect of the –913 SNP in a subgroup who had participated in a study with measurement of IMCL (24). In these 71 nondiabetic individuals, the AA subgroup had a significantly lower IMCL in tibialis anterior muscle compared with the GA + GG subgroup (3.36 ± 0.35 vs. 4.21 ± 0.31; P = 0.04; Table 4Go). A similar trend was found for IMCL in soleus, which was not statistically significant, however (10.40 ± 0.93 vs. 12.32 ± 0.81; P = 0.23; Table 4Go). In a multivariate regression analysis, the –913 SNP remained an independent determinant of IMCL (tibialis anterior muscle) after adjusting for sex, percent body fat, and VO2max (P = 0.03; Table 4Go). Due to the small number of individuals in this cohort, an effect of the –913 SNP on parameters of obesity in male carriers of the G allele was not found (data not shown).


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  		TABLE 4. Characteristics of nondiabetic subjects with data on IMCL and aerobic power capacity (stratified by –913 genotype)

 

   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
In the present study we have identified two SNPs in the 5'-flanking region of the human GFAT gene, of which the –913 SNP seems to alter the risk for obesity and IMCL accumulation in male subjects. We have no clear explanation for why the associations were only observed in men. Nevertheless, sex-specific associations of genetic markers with obesity indexes have been previously reported (25). Gender-specific hormonal regulation of body fat metabolism, for example, could mask the effect of the –913 SNP in females.

Obesity is a polygenetic disease, and we could only detect a weak effect of the –913 SNP on measures of obesity by stratification into smaller subgroups (26, 27). It cannot be excluded that the results we obtained are a chance finding. However, we have a power of 71% to detect an effect of the –913 SNP on body fat content in the male subgroup. Because this is the first report of an association of this polymorphism with body fat content, this weak effect has to be replicated in independent, larger cohorts.

The function of the 5'-flanking region containing the –913 SNP in human GFAT promoter activity regulation is not known. It is possible that the G/A base substitution changes a transcription factor-binding site, thereby affecting GFAT mRNA levels. A search for potential binding sites at position –913 with MatInspector V2.2 (28) revealed a GATA transcription factor-binding motif that is abrogated by the A->G substitution. However, the functional relevance of this putative promoter region and the impact of the –913 SNP on the activity of the GFAT promoter have to be proven.

An explanation for the altered GFAT protein expression and an increased risk for obesity has been provided recently by Rossetti and colleagues (10); activation of the HBP by glucosamine or short-term overfeeding in rats down-regulated skeletal muscle enzymes for fatty acid oxidation and oxidative phosphorylation. These transcriptional changes were accompanied by a marked decrease in whole body energy expenditure. Thus, increased levels of GFAT protein, possibly caused by the –913 SNP, may enhance nutrient-dependent activation of the HBP and lead to reduced energy expenditure and higher risk for obesity in male –913 G allele carriers. However, in our study, data for glucose/lipid oxidation obtained by indirect calorimetry performed during the hyperinsulinemic-euglycemic clamp showed no association with the –913 SNP. Therefore, the effect of the –913 SNP on GFAT promoter activity and that on GFAT protein expression remain to be determined.


   Acknowledgments
 
We thank N. Stefan and O. Tschritter for critical discussion.


   Footnotes
 
This work was supported by Grant 1092-0-0 from Fortüne (to E.D.S.) and Grant SCHL 239/7-1 from the Deutsche Forschungsgemeinschaft. M.S. is currently supported by a Heisenberg Grant from the Deutsche Forschungsgemeinschaft and a grant from the Deutsche Forschungsgemeinschaft (KFO 114/1).

First Published Online December 21, 2004

Abbreviations: BMI, Body mass index; FFA, free fatty acid; GFAT, glutamine:fructose-6-phosphate aminotransferase; HBP, hexosamine biosynthetic pathway; IGT, impaired glucose tolerance; IMCL, intra-myocellular lipid; SNP, single nucleotide polymorphism; UDP-GlcNAc, uridine-5'-diphosphate-N-acetylglucosamine; VO2max, maximal aerobic capacity.

Received January 13, 2004.

Accepted December 15, 2004.


   References
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 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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M. G. Buse
Hexosamines, insulin resistance, and the complications of diabetes: current status
Am J Physiol Endocrinol Metab, January 1, 2006; 290(1): E1 - E8.
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