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Medical Research Council Epidemiology Unit (B.H., K.K.O., N.J.W., M.S.S.), Strangeways Research Laboratory, Cambridge CB1 8RN, United Kingdom; Institut National de la Santé et de la Recherche Médicale U780-IFR69 (B.H.), Faculté de Médecine Paris Sud, 94807 Villejuif, France; and Departments of Paediatrics (K.K.O.), and of Public Health and Primary Care (R.L., M.S.S.), Institute of Public Health, University of Cambridge, Cambridge CB2 2SR, United Kingdom
Address all correspondence and requests for reprints to: Barbara Heude, Institut National de la Santé et de la Recherche Médicale U780, 16 Avenue Paul Vaillant Couturier, 94807 Villejuif cedex, France. E-mail: heude{at}vjf.inserm.fr.
| Abstract |
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Objectives: The aim of this study was primarily to confirm the association with BMI and, secondarily, to study the associations with other indices of body size.
Methods: In a sample of 2797 women and 2203 men aged 3979 participating in the Norfolk arm of the European Prospective Investigation of Cancer, we genotyped three single nucleotide polymorphisms (SNPs) in the IGF2 gene that were previously associated with BMI [6815 A/T, 1156 T/C (G/A), and 820 G/A (ApaI)].
Results: No significant associations were observed between these SNPs and BMI. However, all three SNPs were significantly associated with height (P = 0.03 to 0.001). In a backward elimination regression analysis, two SNPs, 1156 T/C (G/A) and 820 G/A, remained independently associated with height (P = 0.003 and P = 0.038, respectively). Haplotype analysis of these two SNPs showed that carriers of the GA haplotype were shorter than carriers of each of the other three haplotypes (P < 0.001 for all comparisons).
Conclusions: We did not confirm the previously reported associations between IGF2 polymorphisms and BMI. However, our results suggest that common variation in the IGF2 gene may be associated with adult height. IGF2 could be considered as a candidate gene for future research on mechanisms for the association between height and chronic diseases, such as cancer, diabetes, and coronary heart disease.
| Introduction |
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In postnatal life, Igf2 expression in mice is repressed in all tissues except the brain, and deregulation of Igf2 expression results in postnatal overgrowth (6). In pigs, a quantitative trait locus for muscle growth and leanness has been identified in the IGF2 region (7). In humans, IGF2 is biallelically expressed in the liver in postnatal life, and the syndromes of IGF2 under- and overexpression exhibit postnatal growth failure and growth acceleration, respectively (4, 5).
Common allelic variants in IGF2 have been associated with body weight and body mass index (BMI) in large population-based studies. In a study of 2500 United Kingdom middle-aged men, the IGF2 ApaI (820 G/A) minor allele homozygotes had higher serum IGF-II concentrations, and lower BMI and body weight than wild-type homozygotes (8). A subsequent study in the same population investigated 11 other polymorphic markers in IGF2 and found that two further IGF2 single nucleotide polymorphisms (SNPs) were independently associated with BMI (9): minor allele homozygotes at 6815 A/T also had lower BMI, while minor allele homozygotes at 1156 T/C had higher BMI than wild-type homozygotes (9). By contrast, a separate study of 500 healthy men and women found that ApaI 820 G/A minor allele homozygotes had higher fat mass than wild-type homozygotes (10).
Given these inconsistent results, we selected the three IGF2 SNPs previously reported to be independently associated with BMI (9), and aimed to confirm this association in a United Kingdom population of 5000 middle-age men and women. Our secondary aim was to investigate the associations with body fat and also height because some studies had identified associations with height, but these were not highlighted in those reports (8, 10, 11, 12, 13).
| Patients and Methods |
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We analyzed data from the Norfolk arm of the European Prospective Investigation of Cancer (EPIC) prospective cohort study. This study has been described elsewhere (14, 15) but, in brief, is a prospective population study of 25,639 men and women aged between 39 and 79 yr, resident in Norfolk, United Kingdom. Participants were recruited from age-sex registers of general practices in Norfolk as part of the 10-country collaborative EPIC study designed to investigate dietary and other determinants of cancer. Additional data were obtained in EPIC-Norfolk to enable the assessment of determinants of other diseases. The subcohort used for this study is a random sample of 5000 of the participants who were free of disease at baseline (cancer, coronary heart disease, and diabetes), who had completed arrayed DNA samples, completed food frequency questionnaires, and had glycosylated hemoglobin and BMI measured at two clinical assessments separated by an average of 3 yr (16) (Table 1
). All participants gave informed consent.
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All participants completed a detailed health and lifestyle questionnaire, which included a question on birth weight. Anthropometric measurements were taken with participants dressed in light clothing and no shoes. Standing height was measured to the nearest 0.1 cm using a stadiometer, and weight was measured to the nearest 100 g using Salter scales (Salter Brecknell Weighing Products, Fairmont, MN). BMI was calculated as weight (kg)/height (m)2. At follow-up only, sitting height was additionally measured, and leg length was calculated as the difference between overall height and sitting height, plus the height of the measuring stool used for the sitting height measurements. Trunk length was calculated as the difference between leg length and total height. Also at follow-up, a Tanita TBF-531 bioimpedance analyzer (Tanita UK Ltd., Middlesex, UK) was used to determine percent body fat, to the nearest 0.5%.
SNPs choice
In the Northwick Park Heart Study II (NPHSII), the authors conducted a systematic search for variants across the exons, the intron/exon boundaries, and intron three of the IGF2 gene, and identified 12 different markers (9). Four SNPs were associated with BMI, of which two were in strong linkage disequilibrium (LD) (pairwise coefficient = 0.87). Therefore, we selected three SNPs that were not in LD (published as supplemental data on The Endocrine Societys Journals Online web site at http://jcem.endojournals.org): 6815 A/T (rs3842759) at nucleotide position 6815 in the GenBank sequence L15440; 1156 T/C (G/A) at nucleotide position 1156 in the GenBank sequence Y13633; and 820 G/A (ApaI, rs680) at nucleotide position 820 in the GenBank sequence X07868. 6815 A/T and 1156 T/C (G/A) are on intronic regions, whereas 820 G/A (ApaI) is on exon 9.
Genotyping
All SNPs were genotyped using Custom TaqMan assays (Applied Biosystems, Warrington, UK) on an ABI PRISM 7900HT Sequence Detection System (Applied Biosystems). Details for all genotyping primers, probes, and PCR conditions are available upon request from the corresponding author. The three SNPs had a genotyping call rate above 93%, and all of the duplicate controls used in the study set were fully concordant.
Statistical analysis
Each SNP was tested for Hardy-Weinberg (H-W) equilibrium using the appropriate
2 test. We used linear regression to test the association between each genotype (independent variable) and each anthropometric outcome (dependent variable), adjusting for age and sex. We tested the association under an additive (codominant) model by entering each genotype as a quantitative variable (wild/wild, wild/variant, and variant/variant). Recessive models were also tested (i.e. variant/variant vs. carrier of the wild allele). All analyses were performed with SAS version 8.2 (SAS Institute Inc, Cary, NC).
Haplotype analysis was undertaken using the SNPs that remained independently associated with height after a backwards elimination regression analysis. Because phase was unknown, assignment of haplotype probabilities was performed using the SNPHAP program (http://www-gene.cimr.cam.ac.uk/clayton/software/) (17). We then used the "qhapipf" program in STATA (Stata Corp LP, College Station, TX) to test whether the haplotypes explained more of the variance in height than the genotypes considered independently (18). Finally, tests for main haplotype effects were performed using a linear model, adjusted for age and gender, weighted by haplotype probability, and clustered by the individual identification to obtain robust SE values (STATA regression command xi:regres).
| Results |
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The frequencies for the haplotypes corresponding to those two SNPs, and the age and sex-adjusted mean height according to the haplotypes are presented in Fig. 1
. The overall association between haplotypes and height was highly significant (P = 0.0002). The haplotypes explained more of the variability in height than when the SNPs were considered independently (P = 0.039). Mean height of individuals with the haplotype GA (frequency of 18.6%) was significantly lower than that of any other haplotype (P < 0.001 with AG, AA, and GG). Among the remaining haplotypes, only a weak difference was observed between AG and GG (P = 0.075).
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| Discussion |
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It was previously reported in the NPHSII of men only, that the three IGF2 polymorphisms we selected were independently associated with BMI (8, 9, 19). However, our study in a larger number of individuals, including both men and women, did not support that observation. Another study in a Caucasian population showed that the IGF2 ApaI polymorphism was related to fat mass, but the association was in the opposite direction to that in the NPHSII (10). Furthermore, ODell et al. (8) did not find an association between the ApaI polymorphism and body weight in their sample of young adults from NPHSII, in contrast to their older population. They concluded that the effect on BMI might occur only later in life, possibly as a consequence of interaction with environmental factors related to age. Because these factors are likely to vary between populations, gene-environmental interactions could explain the discrepancies observed between the studies. However, in our population with a wide age range of men and women (3979 yr), we did not observe any significant interaction between the effects of age and genotypes. Therefore, the associations identified in the original study between the three SNPs and BMI could be false positives; however, discrepant findings between studies could also occur from differences in subject ascertainment or population structure.
However, consistent with our current findings, those previous studies also found associations between IGF2 polymorphisms and adult height, although these findings were not highlighted in those reports. First, in the NPHSII population, a trend for an association between the 820 G/A (ApaI) and height was found. Consistent with our findings, GG homozygotes tended to be taller than AA (8): the size of the effect (0.7 cm difference; P = 0.10) was comparable to our study, but the sample size of that study was smaller (8). In the same population, a further IGF2 SNP at 1252 T/C AluI, which is in positive LD with 820 G/A (ApaI), was significantly associated with height (P = 0.0019) (11), as were two IGF2, INS and TH, gene region haplotypes (12). Furthermore, in a Hertfordshire United Kingdom population, 820 G/A (ApaI) GG homozygotes tended to be both heavier and taller than AA homozygotes (13). Finally, in the Baltimore Longitudinal Study of Aging, women with the 820 G/A (ApaI) A/A genotype were shorter than G/G carriers (P < 0.05), and a similar trend was observed in men (10).
In the present study, participants were exclusively European, living in the same geographical area in the east of the United Kingdom. Although this is an ethnically homogeneous population, we cannot completely exclude the existence of underlying genetic heterogeneity.
The mechanisms by which the IGF2 gene could be associated with adult height remain to be elucidated. IGFs are peptides that regulate growth, differentiation, and regeneration of cells (20). In particular, placental-specific IGF-II is a major modulator of placental and fetal growth (21, 22). Common variants in the IGF2 gene have been associated with the Beckwith-Wiedemann fetal overgrowth syndrome, and such children are noted to be tall (23, 24). However, if the effect observed here originated in fetal life, one would expect an association with birth weight that we did not find. The absence of this association could be explained by a lack of power in our study because the information on birth weight was missing for more than half of the population. Furthermore, a standardized measure of birth length would have been a much better outcome to test this hypothesis than reported birth weight. Alternatively, IGF2 may impact postnatal growth in infancy, childhood, or adolescence. Children with constitutionally tall stature had significantly higher growth velocity and higher IGF-II levels than children with normal height (25). Garrone et al. (25) suggested that IGF-II might be responsible for overgrowth of children with constitutionally tall stature, having an increase in activity on target tissues, particularly at the level of cartilaginous and bone tissue.
In conclusion, we did not confirm previous results of the association between IGF2 polymorphisms and obesity indexes in adults in our study. Other SNPs in the IGF2 region could be involved, and our limited choice of SNPs does not allow us to exclude a possible role of common IGF2 variation in body weight regulation in adults. However, our results suggest that common IGF2 SNPs may regulate adult height. More studies are needed, especially in populations of healthy infants, children, and adolescents, to investigate the timing of this IGF2 effect on postnatal growth velocity and height. IGF2 should be considered as a candidate gene to explain the associations between adult height and chronic diseases, such as cancer, diabetes, and coronary heart disease (26, 27, 28).
| Footnotes |
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Disclosure Statement: The authors have nothing to declare.
First Published Online May 8, 2007
Abbreviations: BMI, Body mass index; EPIC, European Prospective Investigation of Cancer; H-W, Hardy-Weinberg; LD, linkage disequilibrium; NPHSII, Northwick Park Heart Study II; SNP, single nucleotide polymorphism.
Received September 6, 2006.
Accepted April 26, 2007.
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