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Journal of Clinical Endocrinology & Metabolism, doi:10.1210/jc.2004-1468
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The Journal of Clinical Endocrinology & Metabolism Vol. 90, No. 4 2384-2390
Copyright © 2005 by The Endocrine Society

Is Glutamate Decarboxylase 2 (GAD2) a Genetic Link between Low Birth Weight and Subsequent Development of Obesity in Children?

David Meyre, Philippe Boutin, Agnès Tounian, Marianne Deweirder, Mounir Aout, Béatrice Jouret, Barbara Heude, Jacques Weill, Maite Tauber, Patrick Tounian and Philippe Froguel

Centre National de la Recherche Scientifique 8090-Institute of Biology (D.M., P.B., M.D., M.A., P.F.), Pasteur Institute, 59000 Lille, France; Équipe Avenir 3502 (A.T.), Hôtel-Dieu Hospital, F-75004 Paris, France; Institut National de la Santé et de la Recherce Médicale (INSERM) U563 (B.J., M.T.), Children’s Hospital, 31059 Toulouse Cedex 3, France; INSERM U258-IFR69 (B.H.), Paris Sud Medicine Faculty, 94807 Villejuif, France; Pediatric Endocrine Unit (J.W.), Jeanne de Flandre Hospital, 59000 Lille, France; Department of Pediatric Gastroenterology and Nutrition (P.T.), Trousseau Hospital, 75571 Paris Cedex 12, France; and Imperial College Genome Center and Genomic Medicine (P.F.), Hammersmith Hospital, Imperial College London, London W12 0NN, United Kingdom

Address all correspondence and requests for reprints to: Philippe Froguel, Imperial College Genome Centre and Genomic Medicine, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN, United Kingdom. E-mail: p.froguel{at}imperial.ac.uk.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Low birth weight is a risk factor for obesity and type 2 diabetes. The fetal insulin hypothesis proposes that low birth weight might be mediated partly by genetic factors that impair insulin secretion/sensitivity during the fetal stage, as shown for glucokinase, the ATP-sensitive K+ channel subunit Kir6.2, and the small heterodimer partner genes. Glutamic acid decarboxylase 2 gene (GAD2) overexpression impairs insulin secretion in animals. Recently, polymorphisms in the GAD2 gene were associated with adult morbid obesity. In the present study, we investigated potential effects of the functional –243 A->G polymorphism in the 5' promoter region of the GAD2 gene on fetal growth, insulin secretion, food intake, and risk of obesity in 635 French Caucasian severely obese children from three different medical centers. The case/control study confirmed the association between the GAD2 single-nucleotide polymorphism (SNP) –243 A->G and obesity (odds ratio, 1.25; P = 0.04). In addition, SNP –243 GG children carriers showed a 270 g lower birth weight and a 1.5 cm lower birth height compared with AA carriers (P = 0.009 and P = 0.013, respectively). The relation between birth weight and Z score of BMI was linear in AA carrier children (P = 0.00001) and quadratic (U-shaped curve) in AG/GG carrier children (P = 0.0009). G allele children carriers presented a trend toward lower insulinogenic index with 25% reduction of insulin secretion in response to glucose load compared with A carriers (P = 0.09). Eighteen percent of GG obese carriers vs. 5.7% of AA carriers reported binge eating phenotype (P = 0.04). These results confirm the association between GAD2–243 promoter SNP and the risk for obesity and suggest that GAD2 may be a polygenic component of the complex mechanisms linking birth weight to further risk for metabolic diseases, possibly involving the pleiotropic effect of insulin on fetal growth and later on feeding behavior.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
ALTHOUGH A LOW BIRTH weight was suggested to induce subsequent higher risk for overweight and for type 2 diabetes during adult life, the molecular mechanisms underlying this pathogenic link are actively debated (1, 2). Two major hypotheses have been expressed: the programming and the fetal insulin hypotheses. The programming hypothesis proposes that alterations in fetal nutrition and endocrine status result in developmental adaptations that permanently change structure, physiology, and metabolism, thereby predisposing individuals to cardiovascular, metabolic, and endocrine disease in adult life (3). The programming hypothesis was supported by the fact that people exposed to famine in late or midgestation had reduced glucose tolerance (4) and showed a more atherogenic lipid profile (5), a higher BMI (6), and a higher risk for coronary heart disease (7). Fetal programming of the GH-IGF axis has been proposed to serve as a link between fetal growth and adult-onset disease (8). Indeed, IGFs are nutritionally regulated in the sheep fetus (9), and there are abnormalities in the GH-IGF axis in growth-retarded fetuses and neonates (10). Abnormalities in the GH-IGF axis are associated with metabolic complications including cardiovascular diseases (11, 12) and type 2 diabetes (13). Furthermore, data from both animals and humans suggest that there is programming of the GH-IGF axis (14). Alternatively, because insulin is the main factor during the fetal stage (4), impaired fetal insulin secretion/sensitivity by genetic factors may lead to a decrease in birth weight. The fetal insulin hypothesis was strengthened by the identification of mutations in the glucokinase gene, responsible for both lower birth weight and monogenic type 2 diabetes [maturity-onset diabetes of the young type 2 (MODY2)] subtype or permanent neonatal diabetes, probably mainly through impaired glucose sensing in fetal pancreatic ß-cells (15, 16, 17). Recently, mutations in the ATP-sensitive potassium channel subunit Kir6.2 were found to cause both permanent neonatal diabetes and severe intrauterine growth retardation (18, 19). Except for monogenic diseases, several genes modulating ß-cell function could assess the polygenic background for common forms of low birth weight. A highly polymorphic variable number of tandem repeats (VNTR) locus was described in the 5' region of the insulin gene (INS) (20) modulating INS gene transcription (21). The putative association of the rare class III alleles of the insulin VNTR with either birth weight or type 2 diabetes is rather controversial (22, 23, 24, 25, 26). Interestingly, the most common class I alleles were associated with high fasting insulin levels and with childhood obesity in France (27, 28), and a similar trend was shown with overweight in children from a general French population (29). Mutations of the small heterodimer partner (SHP) gene encoding a protein inhibiting the key ß-cell-expressed hepatocyte nuclear factor-4{alpha} transcription factor activity segregate with higher BMI and modulate birth weight in Japanese MODY subjects (30) as well as in three United Kingdom population-based or obese cohorts (31). Altogether, these data suggest that common gene variants modulating insulin secretion may contribute to both impaired fetal growth and early-onset obesity.

We recently reported data suggesting that the –243 A->G single-nucleotide polymorphism (SNP) in the 5' promoter region of the GAD2 gene encoding glutamate decarboxylase 65-kDa enzyme was associated with morbid obesity in a French adult population. We proposed that the GAD2 at-risk allele enhances GAD2 promoter activity (32), thus increasing consequently the potent inhibitory neurotransmitter {gamma}-aminobutyric acid (GABA) pool that may dysregulate food behavior and decrease insulin secretion. Because childhood obesity seems to have a strong genetic basis (33) and is a strong risk factor for morbid obesity over the life span (34), we assessed the contribution of GAD2 promoter SNP in the development of this condition. Therefore, SNP –243 A->G was genotyped in 635 French Caucasian obese children (defined by BMI ≥ 97th percentile) from three different medical centers. We found that the GAD2 promoter variant was significantly associated with childhood obesity in the French population and also influenced fetal growth, feeding behavior, and possibly insulin secretion.


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

Characteristics of obese children issued from the three medical centers are described in Table 1Go. Children from Lille were significantly (P < 0.05) taller (1.94 ± 1.29) than children from Toulouse (1.06 ± 1.22) or Paris (0.89 ± 1.37). Children from Lille were significantly (P < 0.05) less obese (Z score of BMI, 4.12 ± 1.24) than children from Paris (4.82 ± 1.16) or Toulouse (4.79 ± 1.56). We included in the control group 371 unrelated nonobese and normoglycemic husbands and wives from type 2 diabetes families (mean BMI, 22.9 ± 2.3 kg/m2; mean age, 57.2 ± 13.4 yr; women/men, 223/148) and 243 unrelated nonobese and normoglycemic adult subjects (mean BMI, 23.0 ± 2.2 kg/m2; mean age, 42.5 ± 4.9 yr; women/men, 149/94) issued from 294 families of a general population recruited on a geographical basis in two towns from Northern France, Fleurbaix and Laventie (35). In addition, we genotyped 529 children and young adults (mean Z score of BMI, 0.06 ± 1.25; mean age, 14.74 ± 3.6 yr; women/men, 257/272) issued from the 294 Fleurbaix-Laventie families. We selected in this sample 196 unrelated control children (mean Z score of BMI, –0.35 ± 0.9; mean age, 14.6 ± 2.2 yr; women/men, 100/96). School level distribution (primary school, secondary school, high school, and university) was, respectively, 22.6, 52.3, 16.1, and 9% for parents of 236 obese children and 8.2, 43.1, 14.6, and 34.1% for 246 control adults from Fleurbaix-Laventie.


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  		TABLE 1. Characteristics of the obese children

 
BMI curves were individually established from the health notebook when available. Children with a BMI greater than the 97th percentile of BMI for age and sex reported on the tables of Rolland-Cachera et al. (36) (French general population) were defined as obese as recommended by the European Childhood Obesity Group (ECOG) (37). Age at which BMI exceeded the 97th percentile was defined as the age of obesity onset. Age of rebound was evaluated graphically as the age of upward inflection of the BMI curve (38).

After a 12-h overnight fast, subjects received 1) 1 g glucose/kg if subject’s weight was lower than 50 kg, or 2) 75 g glucose if subject’s weight was higher than 50 kg. During the oral glucose tolerance test (OGTT), blood samples were taken at 0, 30, 60, 90, and 120 min for the measurement of plasma glucose and insulin concentrations. Quantitative measurements of plasma insulin were carried out using double-antibody RIAs. Serum glucose concentrations were measured using a glucose oxidase procedure. Normal glucose tolerance was defined by fasting glycemia lower than 6.1 mmol/liter and by a 2-h post-OGTT glycemia lower than 7.8 mmol/liter, according to World Health Organization 1999 criteria. Insulinogenic index and insulin sensitivity index were calculated according to Seltzer et al. (39) and Matsuda et al. (40), respectively. Binge-eating status was diagnosed during medical examination using Diagnostic Statistical Manual IV (DSM IV) criteria (41). We calculated area under the curve of BMI between 0 and 8 yr if individuals were documented for BMI with at least six measures, including necessarily 0 and 8 yr.

Genotyping

GAD2 –243 A->G SNP was genotyped with the LightCycler assay (Roche Diagnostics, Basel, Switzerland) based on hybridization probes and fluorescence resonance energy transfer between fluorescein and LC Red 640 (Roche Diagnostics) (42). The conditions are available upon request from the authors.

Statistical analysis

Fisher’s exact test was applied to compare allelic frequencies between case and controls (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl). SNPs –243 A->G complied with Hardy-Weinberg proportions. Quantitative trait analyses for Z score of BMI, rebound, obesity onset, and area under the curve of BMI between 0 and 8 yr were performed using the t test (dominant model). A univariate general linear model taking into account gender and gestational age was performed for birth weight, birth height, and ponderal index phenotype analyses. A univariate general linear model taking into account gender, age, puberty stage, and BMI was performed for insulin/glucose parameters. Familial association tests were performed using familial-based association test (FBAT) software (43). The statistical power of FBATs was estimated using the free software TDT power calculator 1.2.1 (44). Regression analysis was carried out using R software (www.r-project.org) to explore the relationship between Z score of BMI and birth weight.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
GAD2 SNP –243 A->G: association studies with obesity

SNP –243 A->G was genotyped in 635 severely obese Caucasian children. From this original sample, 477 unrelated individuals were selected for case control study (274 from Lille, 96 from Paris, and 107 from Toulouse). Children’s SNP genotypes and allele frequencies were compared with those found in 614 normoglycemic nonobese adult controls (32). The SNP –243 G adult morbid obesity at-risk allele was similarly prevalent in obese children (21%) compared with morbidly obese adults (21%) (32) and was significantly more frequent than in the control group [17% in nonobese adults, with an odds ratio (OR) of 1.25 (1.01–1.55); P = 0.04)] (Table 2Go). We decided to use adult control individuals who showed a long-term resistance against obesity. Indeed, lean children can develop obesity later in childhood or in young adulthood. To justify the use of non-age-matched controls and to evaluate whether our data were not a result of a hidden generation effect, we genotyped 196 healthy controls from the north of France general population Fleurbaix-Laventie Ville Santé study (35) and found similar frequencies for the G allele (17.1%) in comparison with control adults (17.3%). Because of the relative small size of the control group of children (n = 196), a trend toward association was observed with childhood obesity [OR, 1.27 (0.94–1.72); P = 0.1].


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  		TABLE 2. Genotypic distribution of the SNP –243 A->G of GAD2 gene between 477 unrelated obese children (BMI ≥ 97th percentile) and 614 unrelated controls.

 
Effect of SNP –243 A->G on birth weight and birth height

We then analyzed the potential effect of the GAD2 SNP –243 A->G on the children’s birth weight and birth height using a univariate general linear model taking into account the gender and the gestational age in the French Caucasian obese children for whom these data were available. We observed an association of the SNP –243 A->G with lower birth weight and height. Indeed, children homozygous for the G allele showed an average decrease of 270 g and 1.47 cm, respectively, compared with homozygote AA carriers (P = 0.009 and P = 0.013, respectively) (Table 3Go). Because SNP –243 G induced a decrease of both birth weight and birth height, no association was observed for the ponderal index at birth (Table 3Go). The obese children homozygous GG showed a 9.5-month delayed age of rebound of adiposity compared with the AA carriers (P = 0.019), defined by the second rise in childhood adiposity. However, at the time of the study (mean age, 10.6 yr), we observed a slightly higher Z score of BMI for GG, AG, and AA carriers. We studied the evolution of BMI between 0 and 11 yr in a subgroup of obese children from Lille. AG/GG carriers were characterized by a lower area under the curve of BMI between 0 and 8 yr (Table 3Go; P = 0.03). Meanwhile, this tendency flipped over at the age of 11 yr, because the BMI of AG/GG carriers becomes higher than AA carriers (28.27 vs. 27.30).


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  		TABLE 3. Quantitative trait studies of the –243 A->G variant in 635 French Caucasion obese children

 
Relation between birth weight and Z score of BMI according to the SNP GAD2 –243 A->G

We first studied the link between birth weight and Z score of BMI in 559 obese children and 480 children and young adults from the general population (total n = 1039). Linear regression model explained well this relationship in the whole sample (n = 1039; Z score of BMI = 0.39 + 0.56 x birth weight; P = 0.0001). The next step was to analyze separately AA carriers and AG/GG carriers. In the AA carrier group, we found that a linear regression model was appropriate and provided an improved fit (n = 697; Z score of BMI = –0.28 + 0.74 x birth weight; P = 0.00001; Fig. 1Go). However, in the AG/GG group, a linear model failed to fit significantly the data (n = 342; P = 0.55). Curvilinear models were, therefore, considered to be more suitable than the linear model. A quadratic polynomial model was adopted as the next simplest form (n = 342; Z score of BMI = 17.97 –9.97 x birth weight + 1.57 x birth weight2; P = 0.0009; Fig. 1Go). This revealed a U-shaped relation between birth weight and Z score of BMI in the AG/GG carrier group (Fig. 1Go) and gave a potential explanation for the absence of linear relation between the two parameters. It should also be noted that a polynomial model was unable to fit the data in the AA carrier group.



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  		FIG. 1. Pattern of relation between birth weight and Z score of BMI according to the GAD2 –243 A->G polymorphism background. The sample included 559 obese children and 480 children and young adults from the general population (total n = 1039). In the AA carrier group, a linear regression model was optimal to fit the data (n = 697; Z score of BMI = –0.28 + 0.74 x birth weight;, P = 0.00001). In contrast, in the AG/GG group, a linear regression model failed to show a significant relationship (n = 342; P = 0.55), which can be better described by a quadratic regression (n = 342; Z score of BMI = 17.97 –9.97 x birth weight + 1.57 x birth weight2; P = 0.0009).

 
Effect of SNP –243 A->G on insulin secretion and insulin sensitivity

Insulin secretion and insulin sensitivity were assessed by the analysis of the insulinogenic index and insulin sensitivity index, respectively, in obese children with normal glucose tolerance. A univariate general linear model analysis was performed to take into account the effects of age, gender, puberty stage, and BMI on insulin levels. Carriers of the G at-risk allele showed a trend toward lower insulinogenic indexes with G carriers showing a 25% reduction of insulin secretion in response to glucose load compared with A carriers (P = 0.09; Table 3Go). No association was observed with insulin sensitivity index.

GAD2 SNP –243 A->G: familial association studies with obesity

To exclude false-positive association caused by population stratification, FBAT was investigated in 365 families with childhood obesity from Lille, including 491 children and 714 parents. Under a dominant model, a trend toward an excess of the at-risk G allele was found in affected offspring with BMI higher than the 99th percentile (Z = –1.48; P = 0.14). In addition, a similar trend was found for both birth weight and insulinogenic index (–1.68 < Z < –1.54 and 0.09 < P < 0.12). According to the sample size and the frequency of at-risk G allele (0.17 and 0.21 in control and obese groups, respectively), the FBAT statistical power to detect an association with a P value of 0.01 under the assumption of a multiplicative model and an OR of 1.25 was 34%, suggesting that a larger familial sample set would be required to have a more significant result.

Effect of SNP –243 A->G on binge eating in the French obese children from Lille

The SNP –243 GG genotype was previously associated with abnormal food intake behavior in adults with morbid obesity (32). Thus, the presence of abnormal binge-eating behavior in obese children from the Lille Center was evaluated by a trained physician during medical examination by an in-house questionnaire administered based on the DSM IV criteria (41). Eighteen percent of GG obese carriers vs. 5.7% of AA carriers reported binge eating (Fisher exact P = 0.06; P = 0.04 under a dominant model) (Fig. 2Go).



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  		FIG. 2. Association studies of the –243 A->G variant with binge eating behavior in obese children. Percentage of each genotype of the –243 A->G SNP in obese children with or without binge eating are represented (Fisher exact P = 0.06). Eighteen percent of GG carriers (n = 16) vs. 10.1% (n = 119) of GA carriers vs. 5.7% (n = 296) of AA carriers showed binge eating behavior. In dominant model, 11.1% of GG and GA carriers vs. 5.7% of AA carriers showed binge eating behavior (Fisher exact P = 0.04)

 

   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
This study first suggests the contribution of GAD2 promoter SNP –243 A->G to the genetic risk for childhood obesity in the French population. The genetic risk for obesity conferred by this SNP is modest (OR = 1.25), but it is in line with previous findings in morbidly obese French adults (OR = 1.30) (32). In the context of such a complex trait having polygenic inheritance, the magnitude of the GAD2 genetic effect corresponds to what is known in type 2 diabetes genetics: both PPAR-{gamma} Pro12 allele and CAP10 at-risk haplotype predisposing risks are in the range of 1.10–1.30 (45, 46). It is noteworthy that in French adults no association with moderate forms of obesity (BMI < 40 kg/m2) was reported (32). The present report of an effect of GAD2 variation on early-onset obesity occurring at a mean age of 10.6 yr should remind us that childhood obesity is a potent risk factor for the development of morbid obesity at the adult age (34). Both conditions may share, at least in part, the same genetic background.

The second finding is the effect of the G allele of the promoter SNP –243 A->G on fetal growth. This effect, if confirmed in other populations, is not marginal, because GG carriers have at birth a 270 g lower weight and 1.5 cm lower height compared with wild-type carriers. This GAD2 effect on birth weight may be higher than previously reported for both the insulin gene VNTR (110–200 g) (23, 24) and the SHP gene (40–210 g) (31), but it is obviously modest compared with the monogenic effect conferred by mutations in glucokinase in MODY families (1100 g) (16). The present data suggest that the increased expression of the GAD2 gene during fetal life may decrease insulin secretion and then contribute to modulate growth. In animals, the overexpression of the GAD2 gene increases GABA release from ß-cells and impairs the first phase of insulin secretion in response to glucose (47). However, this effect may be a result of reduced glutamate availability rather than directly through a direct GABA-mediated effect (48). The mechanisms by which glutamate and/or GABA autocrine/paracrine signaling pathways act on insulin secretion is poorly known, but they may involve a modulation of the communications between {alpha}- and ß-cells. Indeed, the activation of metabotropic glutamate and GABA-B receptors modulates insulin exocytosis through various mechanisms ultimately involving the voltage-dependent Ca2+ channels and G protein-mediated modulation of K-ATP channels (49, 50). We previously observed in nonobese adult controls that GAD2 promoter SNP was associated with lower insulin secretion indexes, and a similar trend, although nonsignificant, was found in morbidly obese adults (32). In obese children, a 25% reduction of insulin secretion was found in G carriers, which is in line with adult data. It is noteworthy that we have OGTT data on only a subset of obese children (n = 322), and our analysis lacks statistical power to be fully conclusive. In addition, we have insulin levels only in childhood (mean age at examination, 10.6 yr), which do not necessarily reflect insulin secretion patterns in fetal life. We found a U-shaped relation in AG/GG carrier children, which didn’t appear in the AA group. This U-shaped curve is because of an enrichment of subjects with low birth weight and high Z score of BMI in the AG/GG carrier group, suggesting that the GAD2 polymorphism –243 A->G could be an important genetic determinant of the observed association between low birth weight and subsequent risk of childhood obesity. A similar U-shaped curve was previously described between birth weight and subsequent risk of type 2 diabetes in adult Pima Indians (51).

The third finding of the present study is the high prevalence of binge eating among GAD2 at-risk allele children carriers. In adults, we previously used the full three-factor eating factor questionnaire (TFEQ) (52) and reported that G carriers were more hungry and less restricted to food than wild-type carriers (32). In addition, we showed that the G at-risk allele of –243 A->G SNP induced a 6-fold increased GAD2 gene promoter activity (32). Supporting these data, an increased GABA level in the central nervous system induced increased food intake and obesity in animal models (53, 54). In children, we used a simplified questionnaire that used DSM IV criteria to diagnose binge-eating behavior (41). It shows that GG obese carriers were more likely to present a food intake behavior phenotype related to binge eating compared with the wild-type subjects. Obviously, this self-reported trait is not as accurate as a meal test for evaluating food intake, but binge eating has been proposed to be a good phenotype for genetic studies of obesity (55).

It has been shown that insulin resistance-induced fasting hyperinsulinemia is a strong predictor for increased weight gain in young Pima Indian (56), Caucasian, and African-American children (57). On the other hand, the increased fasting insulin levels associated with class I alleles of the insulin gene VNTR were associated with obesity in children and with increased weight gain during adolescence (27). Our results suggest that the GAD2 variant –243 G is associated with higher risk to develop childhood obesity and a decreased insulin secretion. To explain this apparent contradiction, we hypothesized that, after birth, –243 G allele induced a major effect on food behavior, which is obviously not the case in fetal life where only potential effects on insulin secretion and thus on fetal growth can be noticed. Thus, the effects of GAD2 SNPs on insulin secretion, if true, are modest and probably unable to protect against excessive energy storage.

Overall, obese children carrying the GAD2 at-risk allele are smaller at birth and have a somewhat delayed rebound of adiposity (although much earlier than nonobese children) (58). However, at the age of examination (10.6 yr), they harbor a slightly higher Z score of BMI, and the study of BMI curves according to the GAD2 –243 A->G genotype suggests an acceleration of weight gain from 10 yr for GA/GG carriers. This suggests that GAD2 variation may significantly modify appetite in childhood, contributing to early-onset obesity. Thus the deleterious effect of GAD2 SNP –243 A->G on fetal growth via the possible inhibition of insulin secretion may be compensated by independent central effects of the same polymorphism on food intake.

In conclusion, we replicated in French severely obese children the association of GAD2 SNP –243 A->G with severe obesity. In this population where data were available, we could show a significant effect on birth weight that may reflect impaired insulin secretion during fetal life. Later in age, an increased orexigenic GABA pool in the hypothalamus may favor the development of childhood obesity. Thus, GAD2 may be a polygenic component of the complex mechanisms linking a lower birth weight to additional risk for metabolic diseases.


   Acknowledgments
 
We thank Myriam Caudrelier for administrative support in funding search. We are indebted to all families who participated in this study. We thank the Hôtel-Dieu Hospital, INSERM EA3502 Unit and Dr. Karine Clément for the DNA extraction from Trousseau Hospital obese children. We thank Claire Levy-Marchal and Delphine Jaquet for helpful discussions.


   Footnotes
 
This work was supported in part by an "Association Française de Recherche et d’Etudes sur l’Obésité-Institut Roche de l’Obésité" research prize.

First Published Online January 25, 2005

Abbreviations: BMI, Body mass index; DSM IV, Diagnostic Statistical Manual IV; FBAT, familial-based association test; GABA, {gamma}-aminobutyric acid; GAD2, glutamic acid decarboxylase 2; MODY2, maturity-onset diabetes of the young type 2; OGTT, oral glucose tolerance test; OR, odds ratio; SNP, single-nucleotide polymorphism; VNTR, variable number of tandem repeats.

Received August 2, 2004.

Accepted January 12, 2005.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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