Human Molecular Genetics, 2001, Vol. 10, No. 14 1491-1501
© 2001 Oxford University Press
Positive associations between single nucleotide polymorphisms in the IGF2 gene region and body mass index in adult males
Human Genetics Research Division, University of Southampton School of Medicine, Duthie Building (MP 808), Southampton General Hospital, Tremona Road, Southampton S016 6YD, UK and 1MRC Epidemiology and Medical Care Unit, Wolfson Institute of Preventive Medicine, St Bartholomew’s and The Royal London School of Medicine and Dentistry, Queen Mary and Westfield College, University of London, Charterhouse Square, London EC1M 6BQ, UK
Received March 30, 2001; Revised and Accepted May 2, 2001.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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We previously demonstrated an association between the insulin-like growth factor 2 (IGF2) gene 3'-untranslated region (3'-UTR) ApaI polymorphism and body mass index (BMI) in over 2500 middle-aged Caucasoid males. In the same cohort, we have now tested association with 11 more markers, including seven novel single nucleotide polymorphisms (SNPs), spanning >30 kb across the IGF2 gene. Three SNPs showed significant positive associations with BMI: 6815 A/T in the IGF2 P1 promoter (P = 0.00012, n = 2394) and the newly identified SNPs 1156 C/T in intron 2 (P = 0.017, n = 1567) and 1926 C/G in the 3'-UTR (P = 0.0062, n = 1872). There was strong pairwise linkage disequilibrium (LD) between the ApaI and 1926 C/G sites, whereas LD between ApaI and 6815 A/T, and between ApaI and 1156 T/C, was minimal. Univariately 6815 A/T, 1156 T/C and ApaI explained 1.03, 1.02 and 0.67% of the variation in BMI. Multi-way analysis of variance (ANOVA) models showed that 6815 A/T and 1156 T/C explained a further 0.4 and 0.8% of the variation beyond that accounted for by ApaI and the association of 1926 C/G with BMI disappeared after adjustment. The 6815 A/T, 1156 T/C and ApaI markers in effect constitute independent affirmations of our original hypothesized candidate gene region. In a stepwise multi-way ANOVA model, all three terms were significantly independently associated with BMI. The total proportion of BMI variance explained by this model was 2.25%, strongly suggesting that IGF2 genetic variation is a significant determinant of body weight in middle-aged males.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Adult obesity is an important determinant of coronary disease risk, type II diabetes, hyperlipidaemia, hypertension and other disease susceptibility in later life (1). Evidence for genetic control of human body weight and composition is well established from adoption, twin and family studies (2). Multiple genes, each contributing only a small proportion of total phenotypic variance, seem to operate through modifying susceptibility; the occurrence of a gene increases the risk of developing a characteristic but is not essential for its expression, nor is it itself sufficient to explain the development of the disease. Differences in genetic susceptibility within a population may therefore determine which individuals are most likely to become obese in any given set of environmental circumstances.
We previously demonstrated an association between the insulin-like growth factor 2 (IGF2) gene 3'-untranslated region (3'-UTR) ApaI polymorphism and body mass index (BMI) in over 2500 middle-aged Caucasoid males in the Northwick Park Heart Study II (NPHSII) (3). The mean BMI of rare (AA) homozygous individuals was 1.1 kg/m2 lower than that of common (GG) homozygous individuals (P = 0.0004, n = 2560), with heterozygotes intermediate. In view of the proximity of the insulin (INS) gene (1.4 kb centromeric to IGF2 on chromosome 11p15), we subsequently investigated two INS polymorphisms, –23/HphI and +1127/PstI (4), in the same cohort, but found no association with BMI (5). The IGF2 ApaI polymorphism, sited 
30 kb downstream of the INS polymorphisms, therefore appears to mark an effect on BMI independent of the INS gene. In 82 normal weight (BMI < 27 kg/m2) women from the Quebec Family Study, Sun et al. (6) found that mean BMI was 1.6 kg/m2 higher in AA homozygotes than in GG individuals (P < 0.03). They also found parallel differences in percentage fat and fat mass. We repeated the test for association of BMI with ApaI genotype in a sample of 397 Caucasoid men and 296 women of ages comparable to the NPHSII men (average 67.5 years) born in and living in Hertfordshire, UK (A. Aihie Sayer, H. Syddall, S. O’Dell, I. Day and C. Cooper, manuscript in preparation). IGF2 genotype was not significantly associated with adult height or weight although there was a trend for men of the AA genotype to be lighter and shorter than those of the GG genotype (mean weight of AA individuals was 2.1 kg lower than that of GG individuals, P = 0.61). The patterns were reversed in the women (mean weight of AA individuals was 4.7 kg higher than that of GG individuals, P = 0.16). These results are therefore consistent with previous findings (3,6) although the small number of subjects would not be expected to attain statistical significance.
Collectively these results suggest that variation in the IGF2 gene influences body mass and composition. Our prior hypothesis is that a site or sites contributing to the determination of BMI lies within the IGF2 gene region. We have now systematically tested the association of 11 more markers spanning >30 kb across the gene with BMI in 2743 men from NPHSII, in an attempt to locate a putative BMI locus or loci by linkage disequilibrium (LD) mapping. Seven IGF2 single nucleotide polymorphisms (SNPs) are reported here for the first time and previously reported markers comprise three SNPs in addition to ApaI and a CA dinucleotide repeat polymorphism. Throughout this report all SNPs, with the exception of the well known IGF2 ApaI and AluI polymorphisms, are identified with reference to GenBank accession and nucleotide numbers.
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RESULTS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Seven new SNPs in the IGF2 gene
A systematic scan of IGF2 exons 1, 3, 4, 5, 7, 8 and 9 with intron/exon boundaries by single strand conformation polymorphism (SSCP) analysis identified five previously unknown SNPs. One is in intron 2, GenBank accession no. Y13633, nucleotide 1156 T/C. Four lie in the exon 9 3'-UTR: GenBank accession no. X07868, nucleotide 266 C/T; accession no. X07868, nucleotide 1926 C/G; accession no. X07868, nucleotide 2207 C/T; and the last in a 74 nucleotide unpublished sequence identified by us at accession no. X07868 between nucleotides 3750 and 3751 (see footnote to Table 7). We have designated this SNP 3750ex A/G. A scan of
5.5 kb of the 5' end of intron 3 by denaturing high performance liquid chromatography (DHPLC) identified two more SNPs which we report here for the first time, at GenBank accession no. Y13633, nucleotide 2482 T/C and accession no. Y13633, nucleotide 2722 C/T. Locations of the newly identified SNPs, together with four published SNPs and a CA repeat polymorphism, are shown in Figure 1.
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Three new positive SNP associations with BMI
Variation in mean BMI with respect to SNP genotypes in men drawn from the 2743 subjects of the NPHSII are shown in Table 1. Apart from the positive association with ApaI which we reported previously (P = 0.0004, n = 2560) (3), three other SNPs showed a significant positive association with BMI. In two of these, like ApaI, the rare homozygotes had a lower mean BMI than common homozygotes, with heterozygotes showing intermediate values. At the 6815 A/T site in the P1 promoter [named +2331 A/T by its discoverers (7), with reference to the INS start site at nucleotide +1], TT homozygotes had a mean BMI 1.3 kg/m2 lower than AA (P = 0.00012, n = 2394). At the new 1926 C/G site in the 3'-UTR, GG homozygotes had a mean BMI 1.0 kg/m2 lower than CC homozygotes (P = 0.006, n = 1872). At the third SNP, 1156 T/C, a new site in intron 2, rare CC homozygotes had a mean BMI 0.6 kg/m2 higher than TT homozygotes (P = 0.017, n = 1567). None of the other SNPs tested showed significant association with BMI (P < 0.05).
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In order to obtain some indication that none of the associations were a spurious result of population stratification or admixture, which often has a geographical basis, separate mean BMI values were determined for common and rare homozygote groups from each of the nine NPHSII general practice centres around the UK. The difference between common and rare homozygote mean BMIs for each of the three positively associated SNPs is shown to scale on a map of the UK at the approximate location of the general practice of origin in Figure 2. For ApaI, mean BMI was consistently higher in common compared with rare homozygotes and the same applied to 6815 A/T, with the exception of Carnoustie, and for 1926 C/G, with the exception of Parkstone. In the case of 1156 C/T, rare homozygotes had higher mean BMI in all centres except Carnoustie and Parkstone.
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Frequency of biallelic CA repeat polymorphism in lean and obese subjects
This 800 bp polymorphic sequence spans most of the region between the ApaI and 1926 C/G sites in the 3'-UTR (8). As it was impractical to genotype the dinucleotide repeat in over 2500 samples using ABI technology, we analysed 47 individuals with BMI < 20 kg/m2 and 47 with BMI > 35kg/m2 taken from extremes of the NPHSII BMI range, to determine allele frequencies in the two groups. The repeat region has 5' and 3' polymorphisms visualized independently only after internal digestion, due to its large size. Rainier et al. (9) reported three common alleles at the 5' end of the repeat: 398 bp, frequency 0.54; 383 bp, frequency 0.25; and 402 bp, frequency 0.18, in an unselected sample of 84 North American individuals. Two other alleles were found at frequencies of 0.01 and 0.02. In our sample, only the three common alleles were present. The frequencies were as follows: in 47 lean individuals (BMI < 20 kg/m2), 398 bp, 0.58; 383 bp, 0.41; and 402 bp, 0.01; and in 47 obese individuals (BMI > 35 kg/m2), 398 bp, 0.70; 383 bp, 0.26; and 402 bp, 0.04. Difference in frequency of the three 5' alleles in the lean and obese groups was not significant (
2 = 4.28, 2 d.f., P = 0.12). At the 3' end of the repeat Rainier et al. (9) reported two common alleles of undisclosed size with frequencies of 0.59 and 0.39 and a third rare allele at frequency 0.02. In our sample, there were only two alleles: 399 bp at frequencies of 0.58 in lean subjects and 0.69 in obese subjects, and 404 bp at frequencies of 0.42 in lean subjects and 0.31 in obese subjects. Difference in frequency of the two 3' alleles in the lean and obese groups was not significant (2 = 1.96, 1 d.f., P = 0.16). Pairwise LD between the two most frequent 5' alleles, 398 and 383, and the two 3' alleles, 399 and 404, in the sample of 94 was very strong (
= 0.97, 2 = 63.52, 1 d.f., P = 1.58 x 10–15).
Pairwise LD of markers with ApaI site
As a preliminary to ascertaining independence of the new associations with respect to the ApaI signal, pairwise LD was tested between all 10 SNPs and ApaI in the full cohort. The coefficients () are given in Table 2. SNPs showing no significant association with BMI, with the exceptions of AluI ( = 0.39) and 2482 A/C ( = –0.34), were in minimal LD with ApaI ( = 0.06–0.14). The positively associated 1926 C/G and ApaI sites in the 3'-UTR were in very strong LD ( = 0.87), as was the CA repeat extending between them (CA and ApaI; = 0.73) in the 72 individuals for whom CA repeat genotype data was available. However, the 6815 A/T site in the P1 promoter, which is very strongly associated with BMI, was only in moderate LD with the ApaI site ( = 0.31). Also, the positively associated 1156 T/C site in intron 2 was not in LD with ApaI ( = –0.09) and only moderately so with 6815 A/T ( = –0.27, P = 1.63 x 10–23, n = 1396). As two of the three new SNPs positively associated with BMI were in strong LD with neither ApaI nor each other, it appeared that these associations might show varying degrees of independence.
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Regression of BMI on positively associated SNP genotypes
To determine whether the three new SNP associations were independent of ApaI, mean BMI was regressed on each SNP genotype with ApaI. Significance tests were based on type III sums of squares. Table 3 shows multi-way analysis of variance (ANOVA) based on ApaI with one other of the positively associated SNPs. ApaI alone explained 0.65% of the variance in BMI. The 6815 A/T SNP was independently associated with BMI and explained a further 0.42% of its variation. The 1156 T/C SNP was also independently associated and explained a further 0.82% of its variation. The 1926 C/G SNP was not significantly associated with BMI after adjustment for ApaI.
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In men with data on all three genotypes, 6815 A/T, 1156 T/C and ApaI univariately explained 1.03, 1.02 and 0.67% of the variation in BMI. A stepwise multi-way ANOVA model, fitted using forward selection with tests of the significance of interaction terms included, showed all three terms to be significantly independently associated with BMI (Table 4). Together they explained 2.25% of the variation. Initially 6815 A/T was the variable most strongly associated with BMI, but the partial R2 indicated that this association was weakened from 1.03 to 0.48%, after adjustment for the other terms. In contrast, the proportion of variance explained by 1156 T/C was largely independent, being reduced only slightly from 1.02 to 0.91% by adjustment. The 1926 C/G SNP did not enter the model as it was not associated with BMI after adjustment for the other terms (P = 0.50).
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Effects of associated SNPs with respect to BMI distribution
In order to determine whether the BMI effects associated with the three SNPs 6815 A/T, 1156 T/C and ApaI were evident in all parts of the population distribution, rare homozygous and heterozygous genotype frequencies were determined in each BMI quintile group: 548 men in quintiles 1 and 5, and 549 in each of quintiles 2, 3 and 4 (Fig. 3). For ApaI and 6815 A/T, in which the rare allele is associated with lower BMI, the frequency of homozygotes decreased across the BMI range from lightest to heaviest quintile. In heterozygotes, the trend was still downward but less marked. In 1156 T/C, in which the rare allele is associated with higher BMI, the homozygote genotype frequency increased markedly from lightest to heaviest quintile, but the trend was not reflected in heterozygotes.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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The IGF2 ApaI polymorphism, previously shown by us to be associated with BMI in 2605 men (3) is located in the 3'-UTR of the gene. We have now completed the first systematic association study of the IGF2 gene involving 10 more SNPs (seven of them novel) and a dinucleotide repeat polymorphism, based on a prior hypothesis that a site or sites contributing to the determination of BMI lies within the IGF2 gene region. Three of the SNPs showed positive association with BMI: the 6815 A/T SNP in the P1 promoter region 5' of exon 1, which lies 26 kb upstream of the ApaI site, our newly reported SNPs in intron 2 1156 T/C (15.7 kb upstream) and in the 3'-UTR, 1926 C/G, 1.1 kb downstream of the ApaI site. The remaining seven SNPs tested showed no significant association with BMI. Some of these were sited close to positively associated SNPs. For example, AluI (not associated) is
100 bp from the positively associated 1156 T/C and in minimal LD with it ( = 0.11, P = 7.31 x 10–5, n = 1314). In the 3'-UTR, 266 C/T (not associated) is 550 bp from ApaI and in minimal LD ( = –0.14, P = 7.21 x 10–11, n = 2083). LD between closely spaced sites (<100 kb) is not substantially related to physical distance, and recombination likelihood owes more to factors such as genetic drift, population admixture, stratification or selection. Kruglyak’s estimate (10) that LD is unlikely to extend beyond an average distance of 3 kb in the general population has led to the assertion that whole-genome LD mapping of common disease genes would be impractical, as 500 000 SNPs would be required to ensure LD with a putative causal site. Use of random markers spaced at 6 kb intervals could well have failed to identify a positive signal accounting for 1–2% of BMI variance at the IGF2 locus, had this been a genome-wide association study. Choosing IGF2 as a candidate gene, selection of certain SNPs spaced at even 1 kb intervals would have failed to identify positive associations with BMI of the magnitude we discovered. Our findings underline the importance of exhaustive SNP testing of a candidate locus in order to establish an association explaining a small proportion of variance in a candidate gene. The associations reported here have yet to be replicated in a separate male sample of comparable size and age, although we have observed the same trend in a smaller cohort (Introduction). However, the direction of variation in mean BMI between rare and common homozygotes for each of the positively associated SNPs seems to be largely consistent throughout general practice centre locations, which span 600 miles (1000 km) north to south across the UK (Fig. 2). This suggests that the associations are not the result of population stratification or admixture, which often has geographical basis or correlates. Positive associations with marker SNPs are suggestive of the presence of a potential aetiological site or sites but the degree of independence of the positive signals remains to be established. An obvious possibility is that a number of widely spaced SNPs, each exhibiting high LD coefficients with BMI, may contribute equally to BMI variance and mark the same causal site. Alternatively, they may independently account for proportions of BMI variance, which would signal the presence of more than one aetiological site. The degree of independence of the new associations from that shown with ApaI was addressed firstly by examining the strengths of pairwise LD (Table 2). The 1926 C/G and ApaI sites were in strong LD, suggesting that these SNPs were likely to mark a single site contributing to BMI. Moderate or absent LD with ApaI shown, respectively, by 6815 A/T and 1156 T/C, raised the possibility that the latter two represented new independent signals. The finding that 6815 A/T and 1156 T/C were only in moderate pairwise LD added support. The proportion of total BMI variance explained by each one was then determined by regression analysis.
In the multi-way ANOVA model (Table 3), the independence of the three new SNP effects from that of ApaI was tested. ApaI alone explained 0.65% of the variance in BMI and 6815 A/T and 1156 T/C remained significant after adjusting for ApaI. The 6815 A/T explained 0.42% of BMI variation above that already explained by ApaI and 1156 T/C explained 0.82% of BMI variance beyond the ApaI contribution. The association of 1926 C/G with BMI disappeared after adjustment for ApaI, indicating that a single BMI locus was in LD with both markers. This had been inferred previously from the discovery of strong pairwise LD between them.
Our hypothesis prior to testing association between the ApaI polymorphism and BMI (3) was that the IGF2 genotype affects weight in the general population. That hypothesis was subsequently supported by our discovery of the positive association. The identification here of further IGF2 SNPs associating with BMI but not subsumed under the ApaI/BMI association in a multivariate analysis, represent independent affirmations of our original hypothesis, on the grounds that it concerns the IGF2 gene or genomic region, not a specific ‘functional’ mutation. In effect, the recognition that more than one haplotype within a region exerts a differential effect on a phenotype constitutes an independent replication test, in the broad sense of testing the relationship of genomic region to trait.
In the stepwise regression analysis, the independence of all three SNPs from each other was tested. Looking univariately in subjects with complete data on all three genotypes, ApaI was the weakest of the three associations (R2 = 0.67%, P = 0.01) while the 6815 A/T and 1156 T/C explained similar amounts of the variance (R2 = 1.03%, P = 0.001 and R2 = 1.02%, P = 0.001, respectively). Hence in the stepwise regression model in Table 4, 6815 A/T was entered first, as marginally, it was the strongest univariately. Once 6815 A/T is in the model, adding 1156 T/C increases R2 to 1.81%. Adding ApaI to 6815 A/T only increases R2 to 1.3%, so ApaI explains the least variance. This is shown in the sequential R2 figures; 1156 T/C explains 0.78% above 6815 A/T and ApaI only contributes a further 0.44%. Hence, although the partial R2 for 6815 A/T indicates that it accounts for the greatest proportion of the variance, it is not independent of the other variables, which reduce the R2 for this SNP from 1.03 to 0.48%. Univariately, 1156 T/C accounts for almost the same proportion of the variance as 6815 A/T (1.02% compared with 1.03%), but in the stepwise regression, the other variables reduce the R2 for this SNP far less, from 1.02 to 0.91%. Hence, 1156 T/C explains the most variance independently. If 1156 T/C is entered into the stepwise regression model first, addition of either ApaI or 6815 A/T increases the R2 to 1.8%, showing that after entry of 1156 T/C, ApaI and 6815 A/T are of equal importance. As all three SNPs remain significant in the stepwise regression, each has some influence on BMI that is independent of the other two. The total proportion of variance in BMI explained by this model (6815 A/T, 1156 T/C and ApaI) is 2.25%.
Genetic influences not confined to the extremes of obesity, but exerting their effect across the whole range of body weight are consistent with polygenic inheritance of body mass. In order to determine whether the influence of the positively associated SNPs operated in all parts of the population BMI distribution, rare homozygous and heterozygous genotype frequencies were determined in each BMI quintile group (Fig. 3). For ApaI and 6815 A/T, the weight lowering effect associated with two rare alleles was apparent in all quintiles, as homozygous genotype frequency decreased steadily with increasing BMI. In the case of 1156 T/C, the homozygous genotype frequency increased from lightest to heaviest quintile. The effect of a single allele in heterozygotes was still evident across BMI quintiles, although less marked than in homozygotes. In contrast, a monogenic autosomal recessive obesity disorder such as leptin deficiency (11) occurs only in rare homozygotes and the morbid obese phenotype only appears in the upper extreme of the BMI range. Heterozygotes are phenotypically normal; the single allele effect is not apparent in any region of the phenotype range. It therefore appears that the IGF2 SNP alleles identified here, although exerting smaller displacements of BMI than would be evident in a single monogenic disorder, do so across the whole BMI range, confirming the relevance of this polygenic effect to the whole population.
On present evidence, the three independent SNP associations with BMI are most likely to arise as a result of LD with separate aetiological sites. There is strong LD between polymorphic loci within the 40 kb span of chromosome 11p15 which contains the TH, INS and IGF2 genes (7). McGinnis and Spielman (12) found allelic variation at loci near the INS VNTR to be highly associated with particular modes in the class I size distribution. Awata et al. (13) found strong LD between INS class I VNTR 1S alleles and TH microsatellite TH01 allele 9 and with IGF2 ApaI allele A. Sten-Linder et al. (14) found strong LD between SNPs 5' of TH and 3' of IGF2, extending over 40 kb. In NPHSII men we found TH01 allele 9 to be strongly associated with INS VNTR class I small subclass alleles (unpublished data), with which IGF2 ApaI allele A is also preferentially associated (13). It is apparent that a haplotype of TH01 allele 9/INS VNTR 1S/IGF2 ApaI allele A may be important in weight determination.
Possibilities exist for functional roles for 6815 A/T in the IGF2 P1 promoter and ApaI in the 3'-UTR, although a functional role for the intron 2 1156 T/C SNP is less likely as it lies in no known regulatory region. To assess possible significance of ApaI as a determinant of circulating insulin-like growth factor II (IGF-II), we previously examined mean serum levels of the gene product with respect to genotype (3). In randomly selected IGF2 ApaI homozygotes from the NPHSII cohort, IGF-II levels were significantly higher in the lighter rare homozygotes than in common homozygotes. Although mouse IGF-II knockouts are smaller and lighter (15), and chimeric IGF-II overexpressing mice are heavier than controls (16), low serum IGF-I concentrations are associated with visceral fat mass in men (17). Thus the IGF2 ApaI genotype correlation would be consistent with what is known about the physiological and pharmacological role of IGF-I in reducing abdominal obesity, especially since both IGF-I and IGF-II mediate their biological effects through the same type 1 IGF receptor.
It is possible that one or more of the SNPs newly associated with BMI may be associated with levels of circulating IGF-II, although variation with respect to these genotypes has not yet been tested. A functional role for the 3'-UTR ApaI or1926 C/G SNP is theoretically possible. Human IGF-II mRNAs are known to be subject to site-specific endonucleolytic cleavage in the 3'-UTR, leading to an unstable 5' product containing the IGF-II coding region and a stable 5' product of 1.8 kb (18). Two sequence elements are required for cleavage: element I, located 2 kb upstream of the cleavage site, and element II, encompassing the cleavage site itself. The cleavage site is located at GenBank accesssion no. X07868, nucleotide 2421, only 1.6 kb downstream of ApaI and barely 300 bp downstream of 1926 C/G. In in vitro studies, Scheper et al. (18) found that deletion of the region between elements I and II did not disrupt the cleavage reaction or interfere with efficiency. ApaI and 1926 C/G lie in this intervening region. However, in vivo, the SNPs could affect binding of regulatory molecules and thus exert a functional role in post-transcriptional regulation of IGF-II levels. Or a variant at or near the mRNA cleavage site, inhibiting degradation, which is in LD with ApaI and 1926 C/G, could also cause the elevation in serum IGF-II observed in the lighter ApaI homozygotes. A connection between serum IGF-II level and BMI remains speculative at present, based on analogy with the known effects of IGF-I on adiposity, described above. Even if LD with a BMI locus found a parallel with circulating peptide levels, an influential role for IGF-II in the determination of BMI cannot be inferred but remains a possibility.
Association of BMI with the P1 promoter polymorphism 6815 A/T presents the possibility of a functional influence on transcription. The 6815 A/T site is situated 5 bp upstream of a second polymorphism, a 5 bp ins/del at nucleotide 6820 (+2336) (4). It is possible that either or both could affect P1 promoter function by effecting a conformational change in DNA. CCAAT/enhancer binding protein 
(C/EBP ) has been identified as a major contributor to postnatal liver-specific activation of the human IGF2 P1 promoter (19) and its recognition site is situated 27 bp upstream of 6815 A/T (20). Control of IGF-II expression could result from the A
T change and/or the 5 bp ins/del altering the affinity of the C/EBP binding site. P1 also contains two elements of 67 nucleotides which form an inverted repeat (IR) (21). A binding protein involved in the suppression of P1 activity specifically binds the two IR elements. If the AT change and/or the 5 bp del were to alter DNA conformation around the IR to affect binding of the inhibitory factor, regulation of IGF-II could accompany the 6815 A/T transversion. While elucidation of possible functional roles for the SNPs awaits further study, the existence of three independent positive associations between LD markers in the IGF2 gene and BMI serves as an important confirmation that variation at this genetic locus is a significant determinant of body weight in middle-aged males.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Study samples
The NPHSII sample comprises healthy adult males aged 51–62 years (22), with the following exclusions: a history of unstable angina or myocardial infarction, regular anticoagulant medication, cerebrovascular disease, malignancy or other conditions precluding informed consent. An unselected group of 2743 individuals were studied from nine widespread UK general practices: Aston Clinton, Camberley, Carnoustie, Chesterfield, Halesworth, Harefield, Parkstone, North Mimms and St Andrews.
Identification of new polymorphisms by SSCP
Forty individuals from the NPHSII cohort, 20 with IGF2 ApaI GG and 20 with the ApaI AA genotype, were selected at random for identification of new SNP markers in the IGF2 gene. Overlapping PCR amplicons of 200–250 bp were designed for scanning of IGF2 exons 1, 3, 4, 5, 7, 8 and 9, including intron/exon boundaries. The whole of the exon 9 3'-UTR was scanned with the exception of the 800 bp CA repeat region at Genbank accession no. X07868, between nucleotides 1122 and 1876. The total sequence scanned by SSCP was 7 kb. PCR amplicons were prepared and analysed by SSCP as described by Whittall et al. (23). Primers used in the amplification of regions in which SSCPs were detected are given in Table 5.
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Identification of new polymorphisms by DHPLC
In later stages of the investigation, SSCP was superseded by DHPLC for mutation detection. Forty further individuals from the NPHSII cohort, 20 with IGF2 ApaI GG and 20 with the ApaI AA genotype, were selected at random for identification of new SNP markers. Overlapping PCR amplicons of
450 bp were designed for scanning of a 5.5 kb region of IGF2 intron 3 contiguous with the region around exon 3 scanned by SSCP. Primers and PCR conditions used in the amplification of regions in which SNPs were detected are given in Table 6. PCR amplicons were duplexed for DHPLC by re-annealing from 95 to 60°C at a rate of 1°C per min. A set of test samples were run through the DHPLC (Varian ProStar Helix, Varian, Walton-on-Thames, UK) at temperatures predicted by the DHPLC Melt program (http://insertion.stanford.edu/melt.html) and 1°C above and below. The optimal temperatures for DHPLC were determined to be the highest temperature that didn’t cause a significantly earlier elution from the column. The set of 40 samples was then run through the system at the optimal temperatures, with a gradient of acetonitrile. Heteroduplexes were identified by direct visualization of the sample chromatograms produced by the DHPLC software. Heteroduplexes elute earlier than homoduplexes, so a heterozygous sample generates two peaks instead of one.
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Identification of SNPs by DNA sequencing
PCRs for sequencing SSCP amplicons were prepared using primers for amplicons upstream (forward primer) and downstream (reverse primer) of the amplicon containing the detected SSCP. Sequencing PCR primers are given in Table 7. For identification of the intron 3 SNPs, the primers used for sequencing were the same as those used for DHPLC (Table 6). Sequencing was performed using an ABI310 automated DNA sequencer (Applied Biosystems, Foster City, CA), with BigDye terminator chemistry. PCR products were cleaned with shrimp alkaline phosphatase (Amersham Pharmacia Biotech AB, Uppsala, Sweden) to dephosphorylate deoxynucleoside triphosphates (dNTPs) carried over from the PCR, and exonuclease I (Amersham Pharmacia Biotech) to destroy primers carried over from the PCR. Samples were then sequenced using the BigDye Terminator Ready Reaction Kit (Applied Biosystems). Sequencing reactions were performed on an MJ Research thermal cycler (PTC-225 DNA Engine TETRAD, MJResearch, Waltham, MA) for 25 cycles of 95°C for 10 s, 50°C for 5 s and 60°C for 4 min. Ramp times were limited to 1°C per s and a final 4°C hold was added. After the sequencing, each reaction was ethanol-precipitated to remove excess dye terminators. Prior to loading on the automated DNA sequencer, pellets were dissolved in 25 µl template suppression reagent (TSR, Applied Biosystems) and heated at 95°C for 4 min to denature, then quenched on ice for 4 min. The samples were then mixed and spun briefly. Finally, samples were loaded into the autosampler tray of an ABI310, and the machine set up to run using POP6 polymer and a 61 cm capillary with 30 s injection time and 120 min run time. The protocol is described in detail in the ABI310 operator’s manual. Polymorphisms were detected by multiple alignment of sequences using ClustalX (24) followed by verification on original sequence chromatograms.
IGF2 exon 3 AluI polymorphism genotyping
In the earliest phase of our investigations, genotyping of polymorphisms was routinely done by PCR and restriction digest of the product, followed by electrophoresis. We have since adopted amplification refractory mutation system (ARMS) assays using much smaller quantities of template DNA. The AluI polymorphism is a TC transition at nucleotide 1252 on GenBank accession no. Y13633, and we found the T allele (presence of the cutting site) to be common (frequency 0.53). Lucassen et al. (4) reported that the non-cutting allele C is common; frequency 0.6. Primers (forward, 5'-CCCAGGGGCCGAAGAGTCA-3' and reverse, 5'-GCTGAGCTGGCAGCGATTCA-3') were obtained from MWG Biotech (Milton Keynes, UK). PCR amplification was in 96-well Omniplates (Hybaid, Teddington, UK), each 10 µl reaction containing 40 ng of genomic DNA, 2.0 mM MgCl2, 50 mM KCl, 10 mM Tris pH 8.3, 0.01% gelatin, 200 µM each dNTP, 8 pmol each primer and 0.2 U of Taq polymerase (Gibco, Paisley, UK). PCR cycling conditions were as follows: 30 cycles at 94°C for 1 min, 62°C for 1 min, 72°C for 45 s and 1 cycle at 72°C for 10 min. AluI restriction enzyme and buffer were obtained from Boehringer (Mannheim, Germany) and 10 µl digests containing 3 U enzyme were incubated for 18 h at 37°C.
IGF2 3'-UTR CA repeat polymorphism genotyping
A region of 803 bp encompassing the CA repeat polymorphism at GenBank accession no. X07868, between nucleotides 1122 and 1876 (8), was amplified from a 5932 bp diluted PCR amplicon prepared from genomic DNA stocks as described below. Ninety-four samples were genotyped, 47 from individuals with BMI < 20 kg/m2 and 47 with BMI > 35kg/m2. PCR conditions and primer sequences used were as described by Rainier et al. (9). The dinucleotide repeat region has 5' and 3' polymorphisms visualized independently only after internal digestion, due to its large size. Accordingly the forward primer was 5'-labelled with a HEX fluorophore, and the reverse primer was 5'-labelled with FAM (MWG Biotech). Four microlitres of the PCR product was restricted with 2 U BstUI enzyme in a 10 µl digest incubated for 1 h at 60°C. Restriction enzyme and buffer were obtained from New England Biolabs, (Herts, UK). After digestion, 1 µl of digestion reaction was combined with 12 µl of formamide dye mix (comprising 24:1 ratio formamide to GS500 TAMRA size standard; Applied Biosystems). The samples were denatured at 95°C for 5 min, cooled on ice for 5 min then loaded on the ABI310. Electrophoresis was through POP-4 polymer (Applied Biosystems) in a 50 cm capillary for 35 min using the standard POP-4 Filter set C run module. Following electrophoresis, samples were sized using Genotyper software (Applied Biosystems). The protocol is described in detail in the ABI310 operator’s manual.
DNA templates for ARMS PCR
Genotyping of all other SNPs was by ARMS assay (25). Assays for the 5' SNPs were performed on genomic DNA. The assays for the intron 2 and intron 3 SNPs and the four SNPs in the 3'-UTR were performed on diluted long PCR amplicons prepared from genomic DNA stocks. The assays for the intron 2 and intron 3 SNPs were performed on an amplicon of 5751 bp and the 3'-UTR polymorphisms on an amplicon of 5932 bp. Primers were obtained from MWG Biotech as follows for the intron 2/exon 3/intron 3 template: forward primer IGF2-I3LongA-650F, 5'-TGAAGTTTTTCTCTGTTGCACCCTGGAC-3'; reverse primer IGF2-I3LongA-6400R, 5'-GGGGTTTCAGACCAATGCCTGAATTTTA-3'. For the exon 9/3'-UTR template: forward primer IGF2EX9LongF, 5'-CCGTCGCAGCCGTGGCATCGTTGAG-3'; reverse primer IGF2EX9LongR, 5'-GGGTGCGGGGAGAGCCAGTGTTGAA-3'. Amplification was in 96-well Omniplates (Hybaid), each 20 µl reaction containing 25 ng of DNA, using a method essentially as described by Cheng et al. (26).
SNP genotyping by ARMS PCR
Primers were obtained from MWG Biotech. Allele-specific and common primers used in each of the assays together with control PCR primers compatible with those of the ARMS reaction, are given in Table 8. For 1156 T/C, 2482 A/C and 2722 C/T SNPs, where the common primer also served as one of the control primers, the concentration of the paired control primer was reduced to 1/10 of the other primers (0.8 pmol/10 µl), to prevent possible rate limitation of the ARMS reaction. For ARMS assays based on long PCR templates, product was diluted 1:100 in water and 3 µl was dried into microplates prior to addition of PCR mix. For ARMS assays based on genomic DNA template, 2.5 µl of a standardized 10 ng/µl array was used. All ARMS PCR reactions were set up in pairs of 384-well microplates (GRI, Braintree, UK), which accommodate four arrays of 96 DNA samples, with one allele-specific reaction in each plate. Each 10 µl reaction contained 1.2 mM MgCl2, 50 mM KCl, 10 mM Tris pH 8.3, 0.01% gelatin, 200 µM each dNTP, 8 pmol each primer and 0.2 U of Taq polymerase (Gibco). An oil overlay was not used, to facilitate passive transfer of PCR samples to the electrophoresis gel. Plates were covered with Microseal A film (GRI) and heated lids were used on the 384-well PCR block (PTC-225 DNA Engine TETRAD, GRI). PCR cycling conditions were as follows: 1 cycle at 94°C for 6 min, then a variable number of amplification cycles comprising melt at 94°C for 1 min, anneal temperature for 1 min and extension at 72°C for 1 min, followed by a final extension of 72°C for 10 min. Details of the number of amplification cycles and annealing temperatures used in each ARMS reaction are given in Table 8. Use of a long PCR template required the number of cycles to be shortened to between 15 and 25, in order to retain allele-specific amplification.
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Microplate array diagonal gel electrophoresis (MADGE)
AluI digestion products were electrophoresed in 96-well MADGE gels (27) as described previously for ApaI genotyping (3). We have since developed a 192-well MADGE gel which accommodates the dual products of ARMS reactions from an 8 x 12 array of samples (28) and most recently a 384-well gel, in which four matrices of 8 x 12 wells accommodate the two ARMS products of two 96-well arrays. The procedure using 384-well gels is described by Gaunt et al. (29) (http://research.bmn.com/tto). After electrophoresis, 5% polyacrylamide 384-well MADGE gels were post-stained in ethidium bromide and examined on a Fluorimager 595 (Molecular Dynamics, Sunnyvale, CA) for visualization of fragments. Excess stain was drained off and the wet gels scanned using a photomultiplier tube voltage setting of 800 V with a 514 nm band pass excitation filter and 610DF30 band pass emission filter. Normal sensitivity scan mode and 100 µm resolution scan settings were used. We have collaborated with Phoretix International in the design of a software package for analysis of electrophoresis bands in lanes arrayed in the 192-well MADGE format (28). Analysis of 384-well arrays simply involves separate analyses of the two 192-well arrays on each gel image.
Statistical analysis
The 2 test of Hardy–Weinberg equilibrium was applied to genotype data. Univariate associations between BMI and each SNP genotype were assessed by one-way ANOVA. Results are presented as means and SD. Pairwise coefficients of LD () between IGF2 ApaI and the other SNPs were estimated as described by Chakravarti et al. (30). To determine whether the SNPs significant in univariate analysis explained further variation in BMI above that attributed to ApaI, multiway ANOVA models including ApaI were fitted using forward selection and each SNP was then added individually to the model. The increase in the model R2 was used to determine the proportion of variance explained by the addition of the new term. A stepwise multi-way ANOVA model was fitted to determine the independence of the associations with BMI. Sequential R2 terms were calculated to show the proportion of variance explained as each term entered the model, and partial R2 to explore the independence of these effects.
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ACKNOWLEDGEMENTS |
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We acknowledge expert technical assistance provided by Ms Sylvia Diaper and Ms Kristy Newman in the completion of this study and from Ms Lesley Hinks in development of the long PCR approach. The work was funded by the British Heart Foundation (grant no. PG/98158), the UK Medical Research Council, the US National Institutes of Health (grant no. NHLBI33014) and DuPont Pharma, Wilmington, USA. The Wessex Medical Trust is thanked for support. S.D.O’D. is a Wessex Medical Trust Senior Research Fellow.
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FOOTNOTES |
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+ To whom correspondence should be addressed. Tel: + 44 23 8079 6425; Fax: + 44 23 8079 4264; Email: S.D.O’Dell@soton.ac.uk
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REFERENCES |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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