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Impact of Common Polymorphisms in Candidate Genes for Insulin Resistance and Obesity on Weight Loss of Morbidly Obese Subjects after Laparoscopic Adjustable Gastric Banding and Hypocaloric Diet

Dipartimento di Medicina Sperimentale e Clinica (G.S., F.A., C.R., M.L.H.), Università Magna Græcia di Catanzaro, 88100 Catanzaro, Italy; Divisione di Medicina Interna (L.P., P.V., V.G., M.M., F.F.), Divisione di Chirurgia Generale (M.P., G.F.), Istituto di Ricovero e Cura a Carattere Scientifico Ospedale San Raffaele, 20132 Milano, Italy; Department of Internal Medicine (M.C., M.L.H.), University of Rome-Tor Vergata, 00133 Rome, Italy; and Universitá di Milano, Cattedra di Medicina Interna and Seconda Divisione di Medicina Interna, Ospedale San Paolo (A.E.P.), 20142 Milano, Italy

Address all correspondence and requests for reprints to: Giorgio Sesti, M.D., Dipartimento Medicina Sperimentale e Clinica, Università Magna-Græcia di Catanzaro, Via Campanella, 115, 88100 Catanzaro, Italy. E-mail: sesti{at}unicz.it; or Franco Folli, M.D., Ph.D., Department of Internal Medicine, HS Raffaele, Via Olgettina 60, 20132 Milan, Italy. E-mail: folli.franco{at}hsr.it.

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Context: It is unknown whether genetic factors that play an important role in body weight homeostasis influence the response to laparoscopic adjustable gastric banding (LAGB).

Objective: We investigated the impact of common polymorphisms in four candidate genes for insulin resistance on weight loss after LAGB.

Design: The design was a 6-month follow-up study.

Setting: The study setting was hospitalized care.

Patients: A total of 167 unrelated morbidly obese subjects were recruited according to the following criteria: age, 18–66 yr inclusive; and body mass index greater than 40 kg/m² or greater than 35.0 kg/m² in the presence of comorbidities.

Intervention: LAGB was used as an intervention.

Main Outcome Measure: Measure of correlation between weight loss and common polymorphisms in candidate genes for insulin resistance and obesity was the main outcome measure.

Results: The following single nucleotide polymorphisms were detected by digestion of PCR products with appropriate restriction enzymes: Gly972Arg of the insulin receptor substrate-1 gene, Pro12Ala of the proliferator-activated receptor- gene, C-174G in the promoter of IL-6 gene, and G-866A in the promoter of uncoupling protein 2 gene. Baseline characteristics including body mass index did not differ between the genotypes. At the 6-month follow-up after LAGB, carriers of G-174G IL-6 genotype had lost more weight than G-174C or C-174C genotype (P = 0.037), and carriers of A-866A uncoupling protein 2 genotype had lost more weight as compared with G-866G (P = 0.018) and G-866A (P = 0.035) genotype, respectively. Weight loss was lower in carriers of Gly972Arg insulin receptor substrate-1 genotype than Gly972Gly carriers, but not statistically significant (P = 0.06). No difference between carriers of Pro12Ala and Pro12Pro proliferator-activated receptor- genotype was observed.

Conclusions: These data demonstrate that genetic factors, which play an important role in the regulation of body weight, may account for differences in the therapeutic response to LAGB.

	Introduction

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DURING THE PAST decade, we have been witnessing an alarming worldwide increase in the prevalence of obesity ("globesity") among both children and adults. Obesity is associated with increased risk for multiple morbidities including diabetes mellitus, dyslipidemia, cardiovascular diseases, cancer, and mortality (1). Weight gain is the consequence of a long-standing imbalance between energy intake and energy expenditure, which are influenced by multiple interactions between genes and environment. Consumption of high-calorie diet and sedentary lifestyle are considered to be the main environmental factors leading to weight gain. On the other hand, genetic factors affecting appetite, energy expenditure, and adipocyte metabolism may predispose individuals to develop obesity.

Weight loss prevents or tempers the severity of many obesity-related morbidities. Unfortunately, treatment of obesity based on dietary measures is unsatisfactory because obesity relapses. Also, the few available antiobesity medications are relatively ineffective, inducing no more than 5–10% of body weight loss, and recidivism after weight reduction is nearly universal.

Laparoscopic adjustable gastric banding (LAGB) has been proposed as a therapeutic approach to achieve durable reduction of body weight in morbidly (grade 3, World Health Organization) obese patients (2). LAGB is a minimally invasive surgical procedure that consists of the placement of a silicone band around the gastric body. The result is a drastic reduction of the volume of the body of the stomach, which increases satiety sensation. We have previous observed that, although LAGB induces a durable weight loss in morbidly obese patients, a significant proportion of these patients (25%) had a relatively modest weight loss (2). It is unknown whether genetic factors that play an important role in body weight homeostasis may account for the differences in the therapeutic effects of LAGB.

One of the several genes that have been implicated in the regulation of body weight is the peroxisome proliferator-activated receptor- (PPARG) gene. PPARG is a ligand-activated transcription factor involved in lipid and glucose metabolism, fatty acid transport, and adipocytes differentiation. A common polymorphism (rs1801282) causing a Pro12Ala substitution has been associated with reduced risk for type 2 diabetes. Many studies have also examined whether the Pro12Ala in PPARG is associated with body mass index (BMI) or other measures of obesity. A recent meta-analysis comprising a total of 19,136 subjects has revealed that the Pro12Ala polymorphism is associated with increased body weight (3). In addition, prospective and intervention studies have shown that the Pro12Ala polymorphism is associated with weight gain over time or weight regain after a diet-induced weight loss (4, 5). By contrast, a lifestyle intervention study in Finnish subjects with impaired glucose tolerance (IGT) have reported that homozygous carriers of the Ala12Ala genotype lose more weight than subjects with the Pro12Pro genotype, whereas the weight loss in carriers of the Pro12Ala genotype was similar to that in subjects with the Pro12Pro genotype (6).

A common polymorphism (rs1801278) in the insulin receptor substrate-1 (IRS1) gene causing a Gly972Arg change has been shown to be associated with type 2 diabetes mellitus and insulin resistance in some, but not all, studies (7, 8, 9, 10). In vitro and ex vivo studies have demonstrated that the Gly972Arg substitution has functional consequence causing impairment in IRS1-associated phosphatidylinositol 3-kinase activity owing to the defective interaction between IRS1 and the p85 subunit of phosphatidylinositol 3-kinase (11, 12). Interestingly, this IRS1 polymorphism appeared also to interact with obesity, potentiating obesity-linked insulin resistance (13, 14).

Uncoupling protein 2 (UCP2) is a member of the mitochondrial inner membrane carrier family, which is expressed in several tissues including adipose tissue, skeletal muscle, liver, and pancreatic islets (15). Like its homologous UCP1, UCP2 mediates mitochondrial proton leak releasing energy stored within the protonmotive force as heat, which, ultimately, results in a decrease in ATP production. It has been reported that the G-866A polymorphism (rs1800795) in the promoter of the human UCP2 gene, which enhances its transcriptional activity resulting in increased UCP2 mRNA levels in human fat cells, is associated with reduced risk of obesity (16).

The immune-regulating and acute phase-inducing cytokine IL-6 is the second most secreted protein "hormone" to be released by human sc adipose tissue, and its serum concentrations are correlated with indices of adiposity (17, 18). Knockout mice lacking the IL-6 gene develop obesity that is reversed by IL-6 replacement at low doses (19). Consequently, IL-6 has been perceived as an auto/paracrine regulator of adipocyte function. A common G-174C polymorphism (rs603573) in the promoter of the human IL-6 gene regulates its transcription in vitro with the G allele showing increased transcriptional activity both under basal condition and in response to inflammatory stimuli (20). It has been reported that the G allele of this polymorphism is more common in lean subjects (21), and that subjects with the G-174G or G-174C genotypes have significantly higher energy expenditure than subjects with the C-174C genotype, possibly contrasting body weight gain (22).

On the basis of the association between the genetic variants described above and obesity, we hypothesized that genetic variations in these candidate genes would influence the therapeutic response to LAGB and hypocaloric diet. To the best of our knowledge, the effect of genetic factors on weight loss after LAGB has not been studied yet. Thus, the objective of this study was to examine the impact of common polymorphisms in four candidate genes on weight loss at 6-month follow-up after LAGB and hypocaloric diet.

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Experimental subjects

The study group consisted of 167 Caucasian subjects with morbid obesity, i.e. grade 3 obesity according to World Health Organization criteria (23), consecutively recruited at the San Raffaele Hospital (Milan, Italy) from November 2002 to March 2004. Clinical characteristics of the study subjects are provided in Table 1. Morbidly obese subjects were considered eligible for LAGB when fulfilling the following criteria: age, 18–66 yr inclusive; BMI, greater than 40 kg/m² or greater than 35.0 kg/m² in the presence of comorbidities (2); and history of at least two previous attempts to lose weight with dietary and medical measures followed by relapse of obesity. Exclusion criteria were as follows: obesity secondary to endocrinopathies (Cushing’s disease or syndrome, hypothyroidism), gastrointestinal inflammatory diseases, risk of upper gastrointestinal bleeding, pregnancy, alcohol or drug addiction, and previous or current malignancies. All measurements were made in the morning after a 12-h fast using standardized methods. The obese subjects were advised to continue their normal diet and avoid alcohol intake and vigorous exercise before the visit. Weight was measured with electric scales. BMI was calculated from the following formula: BMI = weight (kilograms)/height² (meters). Waist circumference was measured at the level midway between the lateral lower rib margin and the iliac crest. Hip circumference was measured at the level of the major trochanters through the pubic symphysis. A 75-g oral glucose tolerance test was performed with 0, 30, 60, 90, and 120 min sampling for plasma glucose, and subjects were classified as normal glucose tolerance, impaired fasting glucose (IFG), IGT, or type 2 diabetes according to the American Diabetes Association criteria (24). Insulin sensitivity was estimated by using the homeostasis model assessment (HOMA) index (25). Eligible patients underwent a preliminary upper gastrointestinal tract evaluation by using x-ray and endoscopy; they were informed of all screening tests and procedures connected with LAGB and follow-up. At the end of the evaluation procedure, suitability for surgery was established by the internist and the surgeon, based on the results of the cardiologist and anesthesiologist visit and risk assessments. Patients also underwent a psychological and psychiatric evaluation, based on structured interviews followed by ad hoc scales of evaluation to exclude major psychiatric disorders (26). After the surgical procedure, they were advised to attend the hospital at fortnight intervals for 2 months and then monthly up to 6 months to be reevaluated by a dietician and a physician. For the first month after LAGB, a semiliquid diet of 800 and 950 kcal/d in women and men, respectively, was prescribed (33% proteins, 19% lipids, 48% carbohydrates). One month after LAGB, a solid diet was reintroduced, and by the third month, the suggested diet was 970 and 1090 kcal/d in women and men, respectively; iron was supplemented on the basis of blood examinations performed during the second month. Diet included 48% carbohydrates (starch or bread), 33% proteins (fat-free parts of different animals and fish), and 19% lipids (olive oil); sweets, cakes, sweetened drinks, alcohol, and animal lipids were forbidden. Patients were advised to eat slowly, to avoid liquids during meals, to use vegetables at each meal and meat or fish at least once a day, and to stop eating when feeling a sense of satiety. All foods had to be cooked without oil, butter, or other lipids. Once or twice weekly, eggs or lean Parma ham or ricotta cheese were allowed in proper quantities. Diets were given by a dietician and a physician with a specific training in obesity treatment and nutrition. The patients were also suggested to take 30 min of physical aerobic activity every day to avoid muscular loss, with a gradual increase over a 1-month period. Physical activity could be gymnastics, swimming, or dancing. Patients were instructed to eat only allowed nutrients and to keep a record of ingested foods, physical activity, and problems encountered.

Analytical determinations

Plasma glucose was measured by the glucose oxidation method (YSI, Inc., Yellow Springs, OH). Triglyceride levels were assayed by an enzymatic technique on a Cobas Fara II Centrifugal Analyser (Cobas Fara II; Roche, Basel, Switzerland). Total cholesterol and HDL-cholesterol levels were assayed by enzymatic automated spectrophotometric methods with a Cobas Fara II. Glycosylated hemoglobin (HbA1c) was assayed by a routine HPLC method. Insulin was assayed by a Microparticle Enzyme Immunoassay (IMX; Abbott Laboratories, Abbott Park, IL) with a monoclonal antibody without cross-reactivity with human proinsulin.

DNA analysis

Genomic DNA was isolated from peripheral blood according to standard procedures. The Gly972Arg polymorphism of the human IRS1 gene was detected by digestion of PCR products with restriction enzyme BstNI as previously described (27). The Pro12Ala polymorphism in exon B of the PPARG gene was detected by digestion of PCR products with restriction enzyme BstUI as previously described (4, 5, 6). The C-174G polymorphism in the promoter of human IL-6 gene was determined by digesting PCR products with restriction enzyme SfaNI as previously described (22). The primers used were 5'-TGA CTT CAG CTT TAC TCT TTG T-3' as upstream primer and 5'-CTG ATT GGA AAC CTT ATT AAG-3' as downstream primer. The G-866G polymorphism in the promoter of human UCP2 gene was determined by digesting PCR products with restriction enzyme MluI (Invitrogen, Milan, Italy) as previously described (28). The primers used were 5'-CAC GCT GCT TCT GCC AGG AC-3' as upstream primer and 5'-AGG CGT CAG GAG ATG GAC CG-3' as downstream primer. All genotypes were done in duplicate with a consensus rate of 99%. Due to unsuccessful genotyping, the subjects examined for the Gly972Arg polymorphism of the IRS1 gene were 167, for the Pro12Ala polymorphism of the PPARG gene were 164, for the C-174G polymorphism of the IL-6 gene were 166, and for the G-866G polymorphism of UCP2 gene were 164. To further validate the fidelity of our genotyping method, the genotype of a fraction of the samples (60 for each gene) was confirmed by direct sequencing.

Statistical analysis

Parametric data are expressed as means ± SD. Normal distribution of variables was checked with the Kolmogorov-Smirnov (Lilliefors) test, and logarithmic transformation was used for those not normally distributed including fasting and 120-min levels of glucose, fasting and 120-min levels of insulin, HOMA, and triglycerides. One-way ANOVA was used to compare differences of continuous variables across three genotypes with post hoc least significant difference (LSD) or Bonferroni correction for multiple comparisons. Differences were also tested after adjusting for age, gender, and BMI by analysis of covariance (general linear model). Multivariate linear regression analysis was performed to evaluate the independent effect of the four polymorphisms on weight loss in a model including gender, age, baseline BMI, and glucose tolerance status as independent variables. Unpaired Student’s t test was used to compare differences of continuous variables between two genotypes. Categorical variables were compared by contingency ² test. The Hardy-Weinberg equilibrium between the two genotypes was evaluated by ² test. All tests were two-sided and a P value less than 0.05 was considered statistically significant. All analyses were performed using SPSS software program version 10.0 for Windows.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Table 1 shows baseline clinical characteristics including gender, age, BMI, waist circumference, waist to hip ratio, and metabolic variables of the study group consisting of 167 unrelated morbidly obese subjects. Of this group, 62.9% of the subjects had normal glucose tolerance, 1.8% of subjects had IFG, 18% of the subjects had IGT, and 17.4% of subjects had type 2 diabetes. At 6-month follow-up after LAGB, BMI changed from 44.6 ± 6.5 kg/m² to an average value of 38.6 ± 5.7 kg/m² (Table 1). In addition, all anthropometric and metabolic variables significantly improved compared with baseline, with the exception of total cholesterol levels (Table 1). Of the 29 subjects who had type 2 diabetes at baseline, nine became normal glucose tolerant at 6-month follow-up, five became IGT, four became IFG, and 11 remained diabetics. Of the 30 subjects who were IGT, 13 became normal glucose tolerant at 6-month follow-up, three became diabetics, one became IFG, and 13 remained IGT. During the 6-month follow-up, the mean number of visits for reevaluation by a dietician and a physician was 5 ± 1; this did not differ between the genotypes of any of the polymorphisms examined. Baseline clinical characteristics including gender, age, BMI, waist circumference, waist to hip ratio, fasting and 120-min levels of glucose, HOMA, and metabolic status did not differ between the genotypes of any of the polymorphisms investigated (data not shown). Table 2 shows baseline BMI and BMI change at the 6-month follow-up, calculated as ([BMI_{6-month follow-up} – BMI_baseline]/BMI_baseline) x 100, according to the four genotypes investigated. The frequency of the Pro12Ala PPARG genotype was 14.1%, and no subjects were homozygous for the Ala12 allele. No difference in body weight loss between the two genotypes was observed at 6-month follow-up after LAGB (Table 2).

The frequencies of the different genotypes at G-174C of the human IL-6 gene were as follows: 45.5% GG, 46.7% GC, and 7.9% CC. Weight loss at 6-month follow-up after LAGB increased according to the dosage of the G allele. Thus, carriers of the G-174G genotype lost more weight as compared with G-174C or C-174C genotype (ANOVA, P = 0.037) (Table 2). The difference in weight loss remained significant after adjustment for age, gender, and baseline BMI (P = 0.028). The difference in weight loss remained significant between carriers of the G-174G genotype and carriers of the C-174C genotype after Bonferroni correction for multiple comparisons (P = 0.05) (Table 2). After pooling subjects carrying G-174C and C-174C genotype, carriers of the G-174G genotype displayed significantly higher weight loss in comparison with carriers of the C allele (percent BMI change 17.5 ± 7.1 vs. 15.1 ± 6.6, respectively; P = 0.034).

The frequencies of the different genotypes at G-866A of the human UCP2 gene were as follows: 51.8% GG, 40.2% GA, and 7.9% AA. After adjustment for age, gender, and baseline BMI, weight loss at 6-month follow-up after LAGB was significantly different among the three genotypes (P = 0.025) (Table 2). After Bonferroni correction for multiple comparisons, carriers of the A-866A genotype lost more weight as compared with G-866G (P = 0.05) (Table 2), suggesting a recessive effect of the A allele. Subjects simultaneously having the UCP2 A-866A/IL-6 G-174G genotypes displayed the highest weight loss as compared with pooled subjects without these favorable genotypes (unpaired Student’s t test P = 0.04). There was no interaction between the UCP2 and IL-6 genotypes as assessed by general linear model. The differences among the genotypes were also evaluated by the univariate ANOVA with post hoc LSD or Bonferroni correction for multiple comparisons (Table 3). Subjects carrying the UCP2 A-866A/IL-6 G-174G genotypes showed the highest weight loss as compared with subjects with the other genotypes, which reached the statistical significance after correction for multiple comparisons with LSD, but not with Bonferroni test. To estimate the independent contribution of the four polymorphisms to weight loss, we carried out a linear regression analysis in a model that also included gender, age, baseline BMI, and glucose tolerance status (Table 4). The results of the multivariate analysis revealed that only the C-174G polymorphism of the IL-6 gene (P < 0.004) and G-866A polymorphism of UCP2 gene (P < 0.035) were independently associated with weight loss. The model accounted for 22.8% of the variation in BMI change after LAGB.

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

We also observed that obese subjects carrying the Gly972Arg polymorphism of the IRS1 gene tended to lose less weight as compared with Gly972Gly carriers but this difference was not statistically significance. Furthermore, it is important to note that multivariate regression analysis in a model including BMI change after LAGB as the dependent variable and the four polymorphisms, gender, age, baseline BMI, and glucose tolerance status as the independent variables revealed that only the C-174G polymorphism of the IL-6 gene, and G-866A polymorphism of UCP2 gene were independently associated with BMI change after LAGB thus indicating that IRS1 polymorphism does not have a significant impact on weight loss.

We did not find any effect of the Pro12Ala polymorphism of the PPARG gene on weight loss after LAGB. These data are consistent with those of two lifestyle intervention studies in which no differences in weight change between carriers of the Pro12Pro and Pro12Ala genotype were reported (5, 6). Indeed, in the Finnish Diabetes Prevention study, subjects with the rare Ala12Ala genotype were shown to lose more weight during the follow-up as compared with the two other genotypes (Pro12Pro and Pro12Ala). Because we did not find any homozygous Ala12Ala, we cannot exclude the possibility that this genotype might affect weight loss after LAGB.

In conclusion, this study provide evidence that promoter polymorphisms of IL-6 (G-174C) and UCP2 (A-866G) genes are associated with increased weight loss in morbidly obese subjects at 6-months follow-up after LAGB. This implies that LAGB was less effective if the subjects were carrying risk genotypes for obesity. Further studies will be needed to replicate these results on a larger scale and in populations with different genetic backgrounds.

	Footnotes

 
This study was supported in part by grants from European Community "EUGENE2" no. LSHM-CT-2004-512013 (to G.S.), Ministero della Sanità (to G.S.), PRIN-COFIN 2002 and 2003 from Ministero dell’Istruzione, Università e Ricerca (to G.S.). F.F. was supported by Ministero della Sanità (Ricerca Finalizzata 2001) and PRIN-COFIN 2001. L.P. was supported by a postdoctoral fellowship of the University of Milan, School of Medicine, and by Ministero della Sanità.

First Published Online June 28, 2005

Abbreviations: BMI, Body mass index; HOMA, homeostasis model assessment; IFG, impaired fasting glucose; IGT, impaired glucose tolerance; IRS1, insulin receptor substrate-1; LAGB, laparoscopic adjustable gastric banding; LSD, least significant difference; PPARG, proliferator-activated receptor-; UCP2, uncoupling protein 2.

Received March 4, 2005.

Accepted June 16, 2005.

	References

Top Abstract Introduction Subjects and Methods Results Discussion References

 

1. Kopelman PG 2000 Obesity as a medical problem. Nature 404:635–643[Medline]
2. Pontiroli EA, Pizzocri P, Librenti MC, Vedani P, Marchi M, Cucchi E, Orena C, Paganelli M, Giacomelli M, Ferla G, Folli F 2002 Laparoscopic adjustable gastric banding for the treatment of morbid (grade 3) obesity and its metabolic complications: a three-year study. J Clin Endocrinol Metab 87:3555–3561[Abstract/Free Full Text]
3. Masud S, Ye S 2003 Effect of the peroxisome proliferator activated receptor- gene Pro12Ala variant on body mass index: a meta-analysis. J Med Genet 40:773–780[Free Full Text]
4. Ek J, Urhammer SA, Sørensen TIA, Andersen T, Auwerx J, Pedersen O 1999 Homozygosity of the Pro12Ala variant of the peroxisome proliferation-activated receptor-2 (PPAR-2): divergent modulating effects on body mass index in obese and lean Caucasian men. Diabetologia 42:892–895[CrossRef][Medline]
5. Nicklas BJ, van Rossum EFC, Berman DM, Ryan AS, Dennis KE, Shuldiner AR 2001 Genetic variation in the peroxisome proliferator-activated receptor- 2 gene (Pro12Ala) affects metabolic responses to weight loss and subsequent weight regain. Diabetes 50:2172–2176[Abstract/Free Full Text]
6. Lindi VI, Uusitupa MIJ, Lindstrom J, Louheranta A, Eriksson JG, Valle TT, Hamalainen H, Ilanne-Parikka P, Keinanen-Kiukaanniemi S, Laakso M, Tuomilehto J, for the Finnish Diabetes Prevention Study Group 2002 Association of the Pro12Ala polymorphism in the PPAR-2 gene with 3-year incidence of type 2 diabetes and body weight change in the Finnish diabetes prevention study. Diabetes 51:2581–2586[Abstract/Free Full Text]
7. Almind K, Bjorbaek C, Vestergaard H, Hansen T, Echwald S, Pedersen O 1993 Amino acid polymorphism of insulin receptor substrate-1 in non-insulin-dependent diabetes mellitus. Lancet 342:828–832[CrossRef][Medline]
8. Jellema A, Zeegers MPA, Feskens EJM, Dagnelle PC, Mensink RP 2003 The Gly972Arg variant in the insulin receptor substrate-1 gene and association with type 2 diabetes: a meta-analysis of 27 studies. Diabetologia 46:990–995[CrossRef][Medline]
9. Zeggini E, Parkinson J, Halford S, Owen KR, Frayling TM, Walker M, Hitman GA, Levy JC, Sampson MJ, Feskens EJM, Hattersley AT, McCarthy MI 2004 Association studies of insulin receptor substrate 1 gene (IRS1) variants in type 2 diabetic samples enriched for family history and early age of onset. Diabetes 53:3319–3322[Abstract/Free Full Text]
10. Florez JC, Sjogren M, Burtt N, Orho-Melander M, Schayer S, Sun M, Almgren P, Lindblad U, Tuomi T, Gaudet D, Hudson TJ, Daly MJ, Ardlie KG, Hirschhorn JN, Altshuler D, Groop L 2004 Association testing in 9,000 people fails to confirm the association of the insulin receptor substrate-1 G972R polymorphism with type 2 diabetes. Diabetes 53:3313–3318[Abstract/Free Full Text]
11. Sesti G, Federici M, Hribal ML, Lauro D, Sbraccia P, Lauro R 2001 Defects of the insulin receptor substrate (IRS) system in human metabolic disorders. FASEB J 15:2099–2111[Abstract/Free Full Text]
12. Hribal ML, Federici M, Porzio O, Lauro D, Borboni P, Accili D, Lauro R, Sesti G 2000 The GlyArg⁹⁷² amino acid polymorphism in insulin receptor substrate-1 affects glucose metabolism in skeletal muscle cells. J Clin Endocrinol Metab 85:2004–2013[Abstract/Free Full Text]
13. Clausen JO, Hansen T, Bjorbaek C, Echwald SM, Urhammer SA, Rasmussen S, Andersen CB, Hansen L, Almind K, Winther K 1995 Insulin resistance: interaction between obesity and a common variant of insulin receptor substrate-1. Lancet 346:397–402[CrossRef][Medline]
14. Baroni MG, Arca M. Sentinelli F, Buzzetti R, Capici F, Lovari S, Vitale M, Romeo S, Di Mario U 2001 The G972R variant of the insulin receptor substrate-1 (IRS-1) gene, body fat distribution and insulin-resistance. Diabetologia 44:367–372[CrossRef][Medline]
15. Fleury C, Neverova M, Collins S, Raimbault S, Champigny O, Levi-Meyrueis C, Bouillaud F, Seldin MF, Surwit RS, Ricquier D, Warden CH 1997 Uncoupling protein-2: a novel gene linked to obesity and hyperinsulinemia. Nat Genet 15:269–272[CrossRef][Medline]
16. Esterbauer H, Schneitler C, Oberkofler H, Ebenbichler C, Paulweber B, Sandhofer F, Ladurner G, Hell E, Strosberg AD, Patsch JR, Krempler F, Patsch W 2001 A common polymorphism in the promoter of UCP2 is associated with decreased risk of obesity in middle-aged humans. Nat Genet 28:178–183[CrossRef][Medline]
17. Fried SK, Bunkin DA, Greenberg AS 1998 Omental and subcutaneous adipose tissues of obese subjects release interleukin-6: depot difference and regulation by glucocorticoid. J Clin Endocrinol Metab 83:847–850[Abstract/Free Full Text]
18. Vozarova B, Weyer C, Hanson K, Tataranni PA, Bogardus C, Pratley RE 2001 Circulating interleukin-6 in relation to adiposity, insulin action, and insulin secretion. Obes Res 9:414–417[Medline]
19. Wallenius V, Wallenius K, Ahren B, Rudling M, Carlsten H, Dickson SL, Ohlsson C, Jansson JO 2002 Interleukin-6-deficient mice develop mature-onset obesity. Nat Med 8:75–79[CrossRef][Medline]
20. Fishman D, Faulds G, Jeffery R, Mohamed-Ali V, Yudkin JS, Humphries S, Woo P 1998 The effect of novel polymorphisms in the interleukin-6 (IL-6) gene on IL-6 transcription and plasma IL-6 levels, and an association with systemic-onset juvenile chronic arthritis. J Clin Invest 102:1369–1376[Medline]
21. Berthier M-T, Paradis A-M, Tchernof A, Bergeron J, Prud’homme D, Després J-P, Vohl M-C 2003 The interleukin 6–174G/C polymorphism is associated with indices of obesity in men. J Hum Genet 48:14–19[CrossRef][Medline]
22. Kubaszek A, Pihlajamaki J, Punnonen K, Karhapaa P, Vauhkonen I, Laakso M 2003 The C-174G promoter polymorphism of the IL-6 gene affects energy expenditure and insulin sensitivity. Diabetes 52:558–561[Abstract/Free Full Text]
23. Anonymous 1995 Physical status: the use and interpretation of anthropometry: report of a WHO expert committee. WHO Tech Rep Ser 854:1–452
24. The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus 1998 Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 21:S5–S19
25. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC 1985 Homeostasis model assessment: insulin resistance and ß-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412–419[CrossRef][Medline]
26. Mazure CM, Halmi KA, Sunday SR, Romano SJ, Einhorn AM 1994 The Yale-Brown-Cornell Eating Disorder Scale: development, use, reliability and validity. J Psychiatr Res 28:425–445[CrossRef][Medline]
27. Marini MA, Frontoni S, Mineo D, Bracaglia D, Cardellini M, De Nicolais P, Baroni A, D’alfonso R, Perna M, Lauro D, Federici M, Gambardella S, Lauro R, Sesti G 2003 The Arg⁹⁷² variant in insulin receptor substrate-1 is associated with an atherogenic profile in offspring of type 2 diabetic patients. J Clin Endocrinol Metab 88:3368–3371[Abstract/Free Full Text]
28. Sesti G, Cardellini M, Marini MA, Frontoni S, D’Adamo M, Del Guerra S, Lauro D, De Nicolais P, Sbraccia P, Del Prato S, Gambardella S, Federici M, Marchetti P, Lauro R 2003 A common polymorphism in the promoter of UCP2 contributes to the variation in insulin secretion in glucose-tolerant subjects. Diabetes 52:1280–1283[Abstract/Free Full Text]
29. Chapman AE, Kiroff G, Game P, Foster B, O’Brien P, Ham J, Maddern GJ 2004 Laparoscopic adjustable gastric banding in the treatment of obesity: a systematic literature review. Surgery 135:326–351[CrossRef][Medline]
30. Tsigos C, Papanicolaou DA, Defensor R, Mitsiadis CS, Kyrou I, Chrousos GP 1997 Dose effects of recombinant human interleukin-6 on pituitary hormone secretion and energy expenditure. Neuroendocrinology 66:54–62[Medline]
31. Marz P, Cheng JG, Gadient RA, Patterson PH, Stoyan T, Otten U, Rose-John S 1998 Sympathetic neurons can produce and respond to interleukin 6. Proc Natl Acad Sci USA 95:3251–3256[Abstract/Free Full Text]
32. Torpy DJ, Papanicolaou DA, Lotsikas AJ, Wilder RL, Chrousos GP, Pillemer SR 2000 Responses of the sympathetic nervous system and the hypothalamic-pituitary-adrenal axis to interleukin-6: a pilot study in fibromyalgia. Arthritis Rheum 43:872–880[CrossRef][Medline]
33. Papanicolaou DA, Petrides JS, Tsigos C, Bina S, Kalogeras KT, Wilder R, Gold PW, Deuster PA, Chrousos GP 1996 Exercise stimulates interleukin-6 secretion: inhibition by glucocorticoids and correlation with catecholamines. Am J Physiol. 271:E601–E605
34. Purohit A, Ghilchik MW, Duncan L, Wang DY, Singh A, Walker MM, Reed MJ 1995 Aromatase activity and interleukin-6 production by normal and malignant breast tissues. J Clin Endocrinol Metab 80:3052–3058[Abstract/Free Full Text]

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