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. 2010 May 11;59(8):2063–2067. doi: 10.2337/db10-0099

BMI at Age 8 Years Is Influenced by the Type 2 Diabetes Susceptibility Genes HHEX-IDE and CDKAL1

Christiane Winkler 1, Ezio Bonifacio 2, Harald Grallert 3, Lydia Henneberger 1, Thomas Illig 3, Anette-Gabriele Ziegler MD 1,4,✉
PMCID: PMC2911059  PMID: 20460429

Abstract

OBJECTIVE

To determine whether HHEX-IDE and CDKAL1 genes, which are associated with birth weight and susceptibility to type 2 diabetes, continue to influence growth during childhood.

RESEARCH DESIGN AND METHODS

BMI, weight, and height at age 8 years expressed as age- and sex-corrected standard deviation scores (SDS) against national reference data and single-nucleotide polymorphism genotyping of HHEX-IDE and CDKAL1 loci were analyzed in 646 prospectively followed children in the German BABYDIAB cohort. All children were singleton full-term births; 386 had mothers with type 1 diabetes, and 260 had fathers with type 1 diabetes and a nondiabetic mother.

RESULTS

Type 2 diabetes risk alleles at the HHEX-IDE locus were associated with reduced BMI-SDS at age 8 years (0.17 SDS per allele; P = 0.004). After stratification for birth weight, both HHEX-IDE and CDKAL1 risk alleles were associated with reduced BMI-SDS (0.45 SDS, P = 0.0002; 0.52 SDS, P = 0.0001) and weight-SDS (0.22 SDS, P = 0.04; 0.56 SDS, P = 0.0002) in children born large for gestational age (>90th percentile) but not children born small or appropriate for gestational age. Within children born large for gestational age, BMI and weight decreased with each additional type 2 diabetes risk allele (∼ −2 kg per allele; >8 kg overall). Findings were consistent in children of mothers with type 1 diabetes (P < 0.0001) and children of nondiabetic mothers (P = 0.008).

CONCLUSIONS

The type 2 diabetes susceptibility alleles at HHEX-IDE and CDKAL1 loci are associated with low BMI at age 8 years in children who were born large for gestational age.

Genome-wide association studies have recently identified common, novel type 2 diabetes susceptibility loci that are likely to predispose one to diabetes via impaired pancreatic β-cell function, impaired insulin secretion, and/or insulin sensitivity (1–3). Some effects occur during fetal growth. For example, the presence of type 2 diabetes risk alleles at the HHEX-IDE and CDKAL1 loci are associated with reduced birth weight, consistent with reduced insulin responses during fetal development (4). This was also observed for the HHEX-IDE locus in our studies of children born to mothers with type 1 diabetes where the fetus is exposed to high and variable glucose concentrations (5). It is unknown whether the gene effects during fetal life persist and whether they are acting in a similar manner after birth. Here we partially address this by determining whether the type 2 diabetes risk alleles at the HHEX-IDE and CDKAL1 loci are associated with growth during childhood in a cohort of children whose mothers or fathers had type 1 diabetes.

RESEARCH DESIGN AND METHODS

Children of parents with type 1 diabetes were recruited in Germany between 1989 and 2000 in the context of the BABYDIAB study (6). Relevant to the current study, birth as well as weight and height data during follow-up were collected from pediatric records that were completed by trained staff at delivery and by pediatricians at visits to the clinic after birth. Children from singleton full-term (≥37 weeks gestational age) births who had a pediatric visit as part of the study between the age of 7.5 and 8.5 years were included in the current analysis. Of these 731 children, genetic data, weight, and height were available from 646 children. This included 386 children who had a mother with type 1 diabetes and 260 children who had a father with type 1 diabetes and a nondiabetic mother. None of the children had a mother with known gestational diabetes. Children who had developed type 1 diabetes prior to age 8 years were not included, because they were lost to follow-up at the onset of their diabetes. All families gave written informed consent to participate in the BABYDIAB study. The study was approved by the ethical committee of Bavaria, Germany (Bayerische Landesärztekammer Nr. 95357).

All children were genotyped for the CDKAL1 SNP rs4712526 and HHEX-IDE SNP rs5015480, rs10882102, and as a control for a type 2 diabetes susceptibility gene that is not associated with fetal growth, also the SLC30A8 SNP rs3802177. Genotyping was performed with the MassARRAY system using the iPLEX chemistry (Sequenom, San Diego, CA) as previously described (5). To control for reproducibility, 16.3% of samples were genotyped in duplicate with discordance rate <0.5%. All SNPs were shown to be in Hardy-Weinberg equilibrium by means of Fisher exact test.

Homeostasis model assessment of insulin resistance (HOMA-IR) was obtained in a subset of children at age 8 years. Children were asked to fast for at least 8 h. Fasting blood glucose was determined locally by a pathology laboratory. Fasting insulin was determined centrally using the Mercodia Ultrasensitive Insulin ELISA (Uppsala, Sweden), a solid-phase two-site enzyme immunoassay, as described in the manufacturer's instructions.

For analysis, data on height, weight, and BMI at follow-up were adjusted for sex and exact age at examination and were expressed as standard deviation scores (SDS) from the mean using German reference data derived from over 34,000 children (7,8). The association between weight-SDS, height-SDS, BMI-SDS, and genotype for each SNP was examined using linear regression, with genotypes coded as 0, 1, or 2 risk alleles and, as a covariate, the type 1 diabetes status of the mother when appropriate. Interaction between birth weight and the HHEX-IDE or CDKAL1 genotypes was tested by the general linear model. Data were also stratified for birth weight expressed as percentiles of the reference German population adjusted for sex and gestational age (9) using the categories small for gestational age (SGA; birth weight <10th percentile of the reference population; n = 68), appropriate for gestational age (AGA; 10th–90th percentile of the reference population; n = 459), and large for gestational age (LGA; >90th percentile of the reference population; n = 120). Gestational age and sex distribution was similar among SGA, AGA, and LGA children. The statistical analysis was performed using SPSS 17.0 (SPSS Inc, Chicago, IL).

RESULTS

Weight, height, and BMI at age 8 years in the cohort were normally distributed and were not significantly different to those of the German reference data (Supplementary Fig. S1, available in an online appendix at http://diabetes.diabetesjournals.org/cgi/content/full/db10-0099/DC1, and Table 1). No differences were observed for weight, height, and BMI at age 8 years between children who had a mother with type 1 diabetes and children who had a father with type 1 diabetes and a nondiabetic mother (Table 1).

TABLE 1.

Characteristics of the study cohort

Children of mothers with T1D Children of fathers with T1D† All children
n (% male) 386 (48.6) 260 (52.7) 646 (50.2)
Median (IQR) gestation in weeks (range) 39 (38–40) 40 (39–41) 39 (38–40)
Birth weight, g 3,572.5 ± 579 3,465.4 ± 510 3,527.6 ± 553
Median (IQR) birth weight percentile (range) 68 (33–91) 54 (23–74) 60 (28–85)
SGA* 35 (9.1) 33 (12.7) 68 (10.5)
AGA* 256 (66.3) 203 (78.1) 459 (71.1)
LGA* 95 (24.6) 24 (9.2) 119 (18.4)
Birth length, cm 51.2 ± 2.7 51.8 ± 2.4 51.5 ± 2.6
8-year height, cm 131.1 ± 5.6 131.8 ± 5.6 131.4 ± 5.6
8-year height-SDS 0.23 ± 0.96 0.35 ± 0.96 0.28 ± 0.96
8-year weight, kg 28.2 ± 4.8 28.5 ± 5.1 28.4 ± 4.9
8-year weight-SDS 0.11 ± 0.93 0.16 ± 0.95 0.13 ± 0.94
8-year BMI 16.4 ± 2.1 16.3 ± 2.2 16.4 ± 2.2
8-year BMI-SDS −0.01 ± 1.0 −0.03 ± 1.0 −0.01 ± 1.0
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Data are mean ± SD or n (%).

*SGA, small for gestational age (<10th percentile); AGA, appropriate for gestational age (10th–90th percentile); LGA, large for gestational age (>90th percentile).

†Children of fathers with type 1 diabetes (T1D) had a mother without T1D or known other diabetes.

The type 2 diabetes risk allele at the HHEX-IDE locus was associated with reduced BMI-SDS at age 8 years in all children. Per risk allele, the BMI-SDS was lower by 0.17 SDS (95% CI, 0.06–0.28; P = 0.004) at age 8 years (Table 2). The association remained significant when the child's maternal diabetes status was included as a covariate (P = 0.004). The same association was observed when a second SNP within the HHEX-IDE locus (rs10882102) was examined (data not shown). The genotypes at the CDKAL1 and SLC30A8 loci were not significantly associated with BMI-SDS in the total cohort.

TABLE 2.

BMI-SDS at age 8 years in relation to fetal genotype in children of parents with type 1 diabetes

BMI-SDS, mean (95% CI)
 Effect per allele BMI-SDS (95% CI) §P †P adjusted
Fetal genotype (no. of T2D risk alleles)
Locus 0 1 2
HHEX-IDE 0.25 (0.06–0.45) −0.04 (−0.15–0.08) −0.12 (−0.26–0.01) 0.17 (0.06–0.28) 0.004 0.004
n = 104 n = 318 n = 218
CDKAL1 0.11 (−0.13–0.34) −0.05 (−0.17–0.07) −0.01 (−0.13–0.11) 0.03 (−0.14–0.09) 0.67 0.69
n = 74 n = 284 n = 88
SLC30A8 0.08 (−0.20–0.35) -0.09 (−0.21–0.03) 0.02 (−0.09–0.14) 0.03 (−0.09–0.16) 0.60 0.54
n = 54 n = 277 n = 305
Birth weight SGA AGA LGA
−0.33 (−0.57–0.10) −0.06 (−0.15–0.03) 0.32 (0.15–0.49) <0.001 <0.001
n = 70 n = 507 n = 132
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§The association BMI-SDS and genotype for each SNP was examined using linear regression, with genotypes coded as 0, 1, or 2 risk alleles. The association BMI-SDS and birth weight was examined using linear regression, with birth weight coded as SGA (small for gestational age; <10th percentile), AGA (appropriate for gestational age; 10th–90th percentile), or LGA (large for gestational age; >90th percentile).

†Adjusted for proband (children who have a mother with type 1 diabetes or children without a mother with type 1 diabetes).

Joint regression analysis showed that 8-year BMI was associated with both birth weight percentile (P < 0.0001) and the HHEX-IDE gene (P = 0.01) also when adjusted for maternal diabetes status. We therefore stratified the children on the basis of their gestational age- and sex-corrected birth weight percentile into small (<10th percentile), appropriate (10th–90th percentile) and large (>90th percentile) for gestational age and analyzed the BMI–gene relationships. Strikingly, there was a very strong association between BMI and the HHEX-IDE genotypes in the LGA children (P = 0.0003), but not in the SGA and AGA children (Fig. 1A; supplementary Tables S1–S3 in an online appendix). A similar association was also observed with CDKAL1 genotypes (P = 0.0001, Fig. 1B; supplementary Tables S1–S3). For CDKAL1, significant interaction was shown between birth weight category and genotype in the general linear model (P < 0.01). For both genes, the type 2 diabetes susceptibility genes were associated with lower BMI-SDS at age 8 years in children born LGA, with the strongest effects seen in children who were homozygous for the susceptibility alleles. Per risk allele, the BMI-SDS was lower by 0.45 SDS (95% CI, 0.22–0.69) for the HHEX-IDE gene and by 0.52 SDS (95% CI, 0.26–0.78) for the CDKAL1 gene in the LGA children. For both the HHEX-IDE and the CDKAL1 genes, a mean BMI above the German reference population mean at 8 years was observed only in the subgroup of children who were LGA and not homozygous for the type 2 diabetes susceptibility alleles. A similar relationship was observed between the HHEX-IDE and the CDKAL1 genes and weight but not height (supplementary Tables S4 and S5, available in an online appendix). No relationship between alleles of the SLC30A8 gene and BMI-SDS were observed with or without stratification for birth weight (data not shown).

FIG. 1.

FIG. 1.

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Association between BMI-SDS at age 8 years and the number of type 2 diabetes risk alleles at the HHEX-IDE locus (A) or CDKAL1 locus (B) after stratification for birth weight. ▴, ●, and × represent children with 0, 1, and 2 type 2 diabetes susceptibility alleles, respectively.

Within the LGA group, both genes were associated with BMI at age 8 years (HHEX-IDE, P = 0.0001; CDKAL1, P = 0.0002) with an adjusted R2 of 0.21 in the joint regression model. Thus, the combination of alleles from both genes showed a dramatic association between the number of type 2 diabetes susceptibility alleles and lower BMI in LGA children (Fig. 2, supplementary Figure S2A and supplementary Table S6, available in an online appendix). LGA children with no type 2 diabetes susceptibility alleles at the HHEX-IDE and CDKAL1 loci had BMIs almost two SDS above the population average, whereas children who had four susceptibility alleles had BMIs that were at or below the population average. Across all birth weight strata, an increased mean 8-year BMI was only seen in children who were LGA and had two or less of the type 2 diabetes susceptibility alleles for HHEX-IDE and CDKAL1. These findings were consistent in children who had a mother with type 1 diabetes (P < 0.0001) and children who had a father with type 1 diabetes and a nondiabetic mother (P = 0.008), and no evidence of interaction between maternal diabetes status and genotype on 8-year BMI was observed. Examination of weight and height in relation to these gene combinations in LGA children found an association with weight and weight-SDS (P = 0.0002; supplementary Figure S2B and supplementary Table S7, available in an online appendix) corresponding to a weight difference of ∼ −2 kg per risk allele and resulting in >8 kg difference between LGA children with no risk alleles (mean weight, 35.7 kg) and those with all four risk alleles (mean weight, 27.5 kg). No association was observed with height-SDS (P = 0.51; data not shown). HOMA-IR was available at age 8 years in 63 LGA children. With this limited data, a similar, but not significant, trend was observed between the number of type 2 diabetes susceptibility alleles at the HHEX-IDE and CDKAL1 loci and both fasting insulin and HOMA-IR (supplementary Figure S3, available in an online appendix).

FIG. 2.

FIG. 2.

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Association between BMI-SDS at age 8 years and the number of type 2 diabetes risk alleles at the HHEX-IDE locus and the CDKAL1 locus after stratification for birth weight.

DISCUSSION

An association between the recently identified type 2 diabetes susceptibility genotypes and growth during childhood was identified. Analysis of weight, height, and BMI in a cohort of children showed that type 2 diabetes susceptibility genotypes at the HHEX-IDE and CDKAL1 loci were associated with reduced BMI and weight at age 8 years. The associations were interactive with birth weight status, suggesting that these genes contribute to both fetal and childhood growth patterns.

Previous studies (10–16) have shown that birth weight is associated with growth and BMI during childhood. Consistent with these studies, SGA children in our cohort were ∼2 kg lighter and LGA children were 2 kg heavier than AGA children at age 8 years (data not shown). There was, however, also a very striking relationship between the HHEX-IDE and CDKAL1 genotypes and 8-year BMI that was found in LGA children. Both genes contributed independently to reduce BMI and weight to around normal in the LGA children but not in the AGA children. Thus, our findings suggest that the type 2 diabetes susceptibility genes HHEX-IDE and CDKAL1 influence homeostasis of body mass when there has been excessive fetal growth. Potentially relevant to this affirmation is that over half the children in our cohort were affected by maternal diabetes, a state that is associated with increased fetal growth via mechanisms that include increased fetal insulin production (17). These children are no longer exposed to diabetic glycemic variations after delivery and are therefore interesting to compare to children of nondiabetic mothers. In this regard, the associations between the HHEX-IDE and CDKAL1 genes and 8-year BMI were consistent in LGA children from mothers with diabetes and children who had a father with type 1 diabetes and a mother without known diabetes. Therefore, although it cannot be excluded that the LGA children from the nondiabetic mothers were also exposed to hyperglycemic stimuli during fetal growth, the associations between genes and BMI appear to be independent of hyperglycemia during pregnancy, further supporting the notion that the genes influence childhood growth in addition to fetal growth.

Our findings are inconsistent with a recent report on children (18). Zhao et al. found increased BMI associated with the type 2 diabetes susceptibility allele of the HHEX-IDE gene and no association between BMI and SNPs of the CDKAL1 gene. It should be noted that, in their study, the association between increased BMI and the HHEX-IDE gene was only observed in children aged 2–6 years and not in older children, whereas we examined children at the age of 8 years. Moreover, inconsistent with ours and other studies (4,5), they did not find an association between the HHEX-IDE gene and birth weight in their cohort. Finally, because our associations were limited to children who were LGA, it is possible that these would be missed in a cohort that is not overly represented by LGA children.

The relationship of our findings to type 2 diabetes susceptibility and pathogenesis is unclear. Many have shown that SGA is associated with increased type 2 diabetes risk (19–22), and some have also suggested that LGA is associated with increased risk (23–25). The relationship of type 2 diabetes susceptibility genes with growth and BMI appears complex, and there is no general rule for the direction of the effect of type 2 diabetes susceptibility and BMI. Ours and previous studies consistently show that SGA is associated with reduced weight, height, and BMI during childhood (10–16). Our data further show that having the full complement of type 2 diabetes susceptibility genotypes for two genes protects against increased BMI at age 8 years. Analogous to this, the protective variant of the type 2 diabetes susceptibility gene PPARG2 is associated with increased BMI (26–28). Thus, while type 2 diabetes is generally associated with increased BMI, there are examples where increased BMI can be associated with reduced type 2 diabetes risk. It is possible that, in such examples, large fat deposits may protect against accumulation in the liver and muscle in children with protective alleles. It is also possible that, although BMI is not increased, other characteristics such as adiposity or insulin sensitivity may be already affected in the children (29,30), or that different gene effects are seen in the subset of children with increased adiposity (28) or under certain dietary conditions such as was found for peroxisome proliferator–activated receptor-γ (31). Relevant to our cohort, which has an increased load of type 1 diabetes–associated genetic susceptibility, it is possible that the relative contribution of genes such as HHEX-IDE and CDKAL1 to pathogenesis may be outweighed by a series of other genes. Finally, longer follow-up of our and, in particular, type 2 diabetes–susceptible cohorts will be required to ascertain if the association of lower weight and BMI with the type 2 diabetes susceptible alleles for the HHEX-IDE and CDKAL1 genes persists or changes after puberty and in adulthood.

In conclusion, we show that the fetal programming associated with the type 2 diabetes susceptibility genes HHEX-IDE and CDKAL1 has prolonged effects during childhood as evidenced by the influence of birth weight status on BMI and weight at age 8 years, and that further programming in association with these genes occurs during childhood when there has been excess fetal growth. These data indicate that there is important genetic control of childhood weight that may act through mechanisms associated with insulin release and action. The relationship of these genetic factors to weight control during childhood appears inconsistent to their association with type 2 diabetes later in life, a finding that requires validation and longer follow-up of cohorts that are susceptible for type 2 diabetes.

Supplementary Material

Online Appendix
supp_59_8_2063__index.html (776B, html)

ACKNOWLEDGMENTS

The work was supported by grants from the JDRF (JDRF No. 1-2006-665), the German National Genome Research Network (NGFN), the Helmholtz Center Munich, German Research Center for Environmental Health, and the Kompetenznetz Diabetes mellitus (Competence Network for Diabetes mellitus) funded by the Federal Ministry of Education and Research (FKZ 01GI0805-07). E.B. is supported by the DFG-Center for Regenerative Therapies Dresden, Cluster of Excellence (FZ 111). No potential conflicts of interest relevant to this article were reported.

C.W. designed the study and the concept, performed acquisition of data, undertook statistical analysis, provided interpretation of the results, wrote and edited the manuscript, and provided critical review of the manuscript for intellectual content. E.B. designed the study and the concept, performed statistical analysis, provided interpretation of the results, wrote the manuscript, and provided critical review of the manuscript for intellectual content. H.G. performed the genotyping and wrote the manuscript. L.H. performed acquisition of data and wrote the manuscript. T.I. performed the genotyping, wrote the manuscript, and provided critical review of the manuscript for intellectual content. A.Z. was the principal investigator, designed the study and concept, undertook the statistical analysis, provided interpretation of the results, wrote the manuscript, and provided critical review of the manuscript for intellectual content.

We thank Annette Knopff and Marina Zwilling (Institut fuer Diabetesforschung der Forschergruppe Diabetes e.V. at Helmholtz Center Munich, Neuherberg, Germany) for data collection and expert technical assistance. We also thank all pediatricians and family doctors in Germany for participation in the BABYDIAB study.

Footnotes

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

REFERENCES

  • 1.Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T, de Bakker PI, Abecasis GR, Almgren P, Andersen G, Ardlie K, Boström KB, Bergman RN, Bonnycastle LL, Borch-Johnsen K, Burtt NP, Chen H, Chines PS, Daly MJ, Deodhar P, Ding CJ, Doney AS, Duren WL, Elliott KS, Erdos MR, Frayling TM, Freathy RM, Gianniny L, Grallert H, Grarup N, Groves CJ, Guiducci C, Hansen T, Herder C, Hitman GA, Hughes TE, Isomaa B, Jackson AU, Jørgensen T, Kong A, Kubalanza K, Kuruvilla FG, Kuusisto J, Langenberg C, Lango H, Lauritzen T, Li Y, Lindgren CM, Lyssenko V, Marvelle AF, Meisinger C, Midthjell K, Mohlke KL, Morken MA, Morris AD, Narisu N, Nilsson P, Owen KR, Palmer CN, Payne F, Perry JR, Pettersen E, Platou C, Prokopenko I, Qi L, Qin L, Rayner NW, Rees M, Roix JJ, Sandbaek A, Shields B, Sjögren M, Steinthorsdottir V, Stringham HM, Swift AJ, Thorleifsson G, Thorsteinsdottir U, Timpson NJ, Tuomi T, Tuomilehto J, Walker M, Watanabe RM, Weedon MN, Willer CJ, Wellcome Trust Case Control Consortium. Illig T, Hveem K, Hu FB, Laakso M, Stefansson K, Pedersen O, Wareham NJ, Barroso I, Hattersley AT, Collins FS, Groop L, McCarthy MI, Boehnke M, Altshuler D: Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet 2008;40:638–645 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Grarup N, Rose CS, Andersson EA, Andersen G, Nielsen AL, Albrechtsen A, Clausen JO, Rasmussen SS, Jørgensen T, Sandbaek A, Lauritzen T, Schmitz O, Hansen T, Pedersen O: Studies of association of variants near the HHEX, CDKN2A/B, and IGF2BP2 genes with type 2 diabetes and impaired insulin release in 10,705 Danish subjects: validation and extension of genome-wide association studies. Diabetes 2007;56:3105–3111 [DOI] [PubMed] [Google Scholar]
  • 3.Pascoe L, Tura A, Patel SK, Ibrahim IM, Ferrannini E, Zeggini E, Weedon MN, Mari A, Hattersley AT, McCarthy MI, Frayling TM, Walker M: RISC Consortium, U.K Type 2 Diabetes Genetics Consortium.K. Type 2 Diabetes Genetics Consortium.K. Type 2 Diabetes Genetics Consortium. Common variants of the novel type 2 diabetes genes CDKAL1 and HHEX/IDE are associated with decreased pancreatic beta-cell function. Diabetes 2007;56:3101–3104 [DOI] [PubMed] [Google Scholar]
  • 4.Freathy RM, Bennett AJ, Ring SM, Shields B, Groves CJ, Timpson NJ, Weedon MN, Zeggini E, Lindgren CM, Lango H, Perry JR, Pouta A, Ruokonen A, Hyppönen E, Power C, Elliott P, Strachan DP, Järvelin MR, Smith GD, McCarthy MI, Frayling TM, Hattersley AT: Type 2 diabetes risk alleles are associated with reduced size at birth. Diabetes 2009;58:1428–1433 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Winkler C, Illig T, Koczwara K, Bonifacio E, Ziegler AG: HHEX-IDE polymorphism is associated with low birth weight in offspring with a family history of type 1 diabetes. J Clin Endocrinol Metab 2009;94:4113–4115 [DOI] [PubMed] [Google Scholar]
  • 6.Ziegler AG, Hummel M, Schenker M, Bonifacio E: Autoantibody appearance and risk for development of childhood diabetes in offspring of parents with type 1 diabetes: the 2-year analysis of the German BABYDIAB Study. Diabetes 1999;48:460–468 [DOI] [PubMed] [Google Scholar]
  • 7.Kromeyer-Hauschild K, Wabitsch M, Kunze D, Geller F, Geiß HC, Hesse V, v. Hippel A, Jaeger U, Johnsen D, Korte W, Menner K, Müller G, Müller JM, Müller M, Niemann-Pilatus A, Remer T, Schaefer F, Wittchen HU, Zabransky S, Zellner K, Ziegler A, Hebebra J: Perzentile für den Body-mass-Index für das Kinder- und Jugendalter unter Heranziehung verschiedener Stichproben. Monatsschr Kinderheilkd 2001;8:807–818 [Google Scholar]
  • 8.Arbeitsgemeinschaft Adipositas im Kindes- und Jugendalter: Body-Mass-Index für deutsche Kinder und Jugendliche. http://www.mybmi.de Accessed 18 November 2008
  • 9.Voigt M, Schneider KT, Jährig K: Analysis of a 1992 birth sample in Germany. 1: New percentile values of the body weight of newborn infants. Geburtshilfe Frauenheilkd 1996;56:550–558 [DOI] [PubMed] [Google Scholar]
  • 10.Strauss RS: Effects of the intrauterine environment on childhood growth. Br Med Bull 1997;53:81–95 [DOI] [PubMed] [Google Scholar]
  • 11.Garn SM, Shaw HA, McCabe KD: Birth size and growth appraisal. J Pediatr 1977;90:1049–1051 [DOI] [PubMed] [Google Scholar]
  • 12.Garn SM: Relationship between birth weight and subsequent weight gain. Am J Clin Nutr 1985;42:57–60 [DOI] [PubMed] [Google Scholar]
  • 13.Binkin NJ, Yip R, Fleshood L, Trowbridge FL: Birth weight and childhood growth. Pediatrics 1988;82:828–834 [PubMed] [Google Scholar]
  • 14.Brody DJ, Flegal KM, Gergen PJ: Birth weight and childhood size in a national sample of 6- to 11-year-old children. Am J Hum Biol 1995;7:293–301 DOI 10.1002/ajhb.1310070305 [DOI] [PubMed] [Google Scholar]
  • 15.Hediger ML, Overpeck MD, McGlynn A, Kuczmarski RJ, Maurer KR, Davis WW: Growth and fatness at three to six years of age of children born small- or large-for-gestational age. Pediatrics 1999;104:e33. [DOI] [PubMed] [Google Scholar]
  • 16.Hirschler V, Bugna J, Roque M, Gilligan T, Gonzalez C: Does low birth weight predict obesity/overweight and metabolic syndrome in elementary school children? Arch Med Res 2008;39:796–802 [DOI] [PubMed] [Google Scholar]
  • 17.Freinkel N: Banting Lecture 1980. Of pregnancy and progeny. Diabetes 1980;29:1023–1035 [DOI] [PubMed] [Google Scholar]
  • 18.Zhao J, Bradfield JP, Zhang H, Annaiah K, Wang K, Kim CE, Glessner JT, Frackelton EC, Otieno FG, Doran J, Thomas KA, Garris M, Hou C, Chiavacci RM, Li M, Berkowitz RI, Hakonarson H, Grant SF: Examination of all type 2 diabetes GWAS loci reveals HHEX-IDE as a locus influencing pediatric BMI. Diabetes 2010;59:751–755 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Burke JP, Forsgren J, Palumbo PJ, Bailey KR, Desai J, Devlin H, Leibson CL: Association of birth weight and type 2 diabetes in Rochester, Minnesota. Diabetes Care 2004;27:2512–2513 [DOI] [PubMed] [Google Scholar]
  • 20.Curhan GC, Willett WC, Rimm EB, Spiegelman D, Ascherio AL, Stampfer MJ: Birth weight and adult hypertension, diabetes mellitus, and obesity in US men. Circulation 1996;94:3246–3250 [DOI] [PubMed] [Google Scholar]
  • 21.Lithell HO, McKeigue PM, Berglund L, Mohsen R, Lithell UB, Leon DA: Relation of size at birth to non-insulin dependent diabetes and insulin concentrations in men aged 50–60 years. BMJ 1996;312:406–410 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Rich-Edwards JW, Colditz GA, Stampfer MJ, Willett WC, Gillman MW, Hennekens CH, Speizer FE, Manson JE: Birthweight and the risk for type 2 diabetes mellitus in adult women. Ann Intern Med 1999;130:278–284 [DOI] [PubMed] [Google Scholar]
  • 23.McCance DR, Pettitt DJ, Hanson RL, Jacobsson LT, Knowler WC, Bennett PH: Birth weight and non-insulin dependent diabetes: thrifty genotype, thrifty phenotype, or surviving small baby genotype? BMJ 1994;308:942–945 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Wei JN, Sung FC, Li CY, Chang CH, Lin RS, Lin CC, Chiang CC, Chuang LM: Low birth weight and high birth weight infants are both at an increased risk to have type 2 diabetes among schoolchildren in Taiwan. Diabetes Care 2003;26:343–348 [DOI] [PubMed] [Google Scholar]
  • 25.Harder T, Rodekamp E, Schellong K, Dudenhausen JW, Plagemann A: Birth weight and subsequent risk of type 2 diabetes: a meta-analysis. Am J Epidemiol 2007;165:849–857 [DOI] [PubMed] [Google Scholar]
  • 26.Deeb SS, Fajas L, Nemoto M, Pihlajamäki J, Mykkänen L, Kuusisto J, Laakso M, Fujimoto W, Auwerx J: A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity. Nat Genet 1998;20:284–287 [DOI] [PubMed] [Google Scholar]
  • 27.Cecil JE, Fischer B, Doney AS, Hetherington M, Watt P, Wrieden W, Bolton-Smith C, Palmer CN: The Pro12Ala and C-681G variants of the PPARG locus are associated with opposing growth phenotypes in young schoolchildren. Diabetologia 2005;48:1496–1502 [DOI] [PubMed] [Google Scholar]
  • 28.Tönjes A, Scholz M, Loeffler M, Stumvoll M: Association of Pro12Ala polymorphism in peroxisome proliferator-activated receptor gamma with Pre-diabetic phenotypes: meta-analysis of 57 studies on nondiabetic individuals. Diabetes Care 2006;29:2489–2497 [DOI] [PubMed] [Google Scholar]
  • 29.Ibáñez L, Ong K, Dunger DB, de Zegher F: Early development of adiposity and insulin resistance after catch-up weight gain in small-for-gestational-age children. J Clin Endocrinol Metab 2006;91:2153–2158 [DOI] [PubMed] [Google Scholar]
  • 30.Lemos JO, Rondó PH, Pereira JA, Oliveira RG, Freire MB, Sonsin PB: The relationship between birth weight and insulin resistance in childhood. Br J Nutr 2010;103:386–392 [DOI] [PubMed] [Google Scholar]
  • 31.Luan J, Browne PO, Harding AH, Halsall DJ, O'Rahilly S, Chatterjee VK, Wareham NJ: Evidence for gene-nutrient interaction at the PPARgamma locus. Diabetes 2001;50:686–689 [DOI] [PubMed] [Google Scholar]

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