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Abstract

  1. Top of page
  2. Abstract
  3. Subjects and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure
  8. REFERENCES

The first genome-wide association study for BMI identified a polymorphism, rs7566605, 10 kb upstream of the insulin-induced gene 2 (INSIG2) transcription start site, as the most significantly associated variant in children and adults. Subsequent studies, however, showed inconsistent association of this polymorphism with obesity traits. This polymorphism has been hypothesized to alter INSIG2 expression leading to inhibition of fatty acid and cholesterol synthesis. Hence, we investigated the association of the INSIG2 rs7566605 polymorphism with obesity- and lipid-related traits in Danish and Estonian children (930 boys and 1,073 girls) from the European Youth Heart Study (EYHS), a school-based, cross-sectional study of pre- and early pubertal children. The association between the polymorphism and obesity traits was tested using additive and recessive models adjusted for age, age-group, gender, maturity and country. Interactions were tested by including the interaction terms in the model. Despite having sufficient power (98%) to detect the previously reported effect size for association with BMI, we did not find significant effects of rs7566605 on BMI (additive, P = 0.68; recessive, P = 0.24). Accordingly, the polymorphism was not associated with overweight (P = 0.87) or obesity (P = 0.34). We also did not find association with waist circumference (WC), sum of four skinfolds, or with total cholesterol, triglycerides, low-density lipoprotein, or high-density lipoprotein. There were no gender-specific (P = 0.55), age-group-specific (P = 0.63) or country-specific (P = 0.56) effects. There was also no evidence of interaction between genotype and physical activity (P = 0.95). Despite an adequately powered study, our findings suggest that rs7566605 is not associated with obesity-related traits and lipids in the EYHS.

The first genome-wide association study for BMI identified a common single-nucleotide polymorphism (SNP) (rs7566605) (G>C), 10 kb upstream of the INSIG2 (insulin-induced gene 2) gene, that was associated with BMI in children and adults (1). Homozygotes for the minor (C) allele (around 10% of the population) at the rs7566605 SNP were roughly 1 kg/m2 heavier than homozygotes for the major G allele or GC heterozygotes. Subsequently, five independent studies in children and adults reported no evidence of association with BMI and a sixth observed statistical association, but only within the overweight individuals of their cohort (2,3,4,5,6). In an attempt to clarify the role of INSIG2 in obesity, Lyon et al. (7) examined the association of SNP rs7566605 with BMI, based on data from nine large observational cohorts consisting of children and adults from eight populations of multiple ethnic backgrounds (n = 16,969). In that study the authors found that the genotype association was significant only in five cohorts (P < 0.05), whereas there was no evidence of statistical association in the remaining cohorts. In the combined analysis, a significant validation of the association of the INSIG2 SNP with increased BMI was observed in both unrelated (P = 0.046) and family-based (P = 0.004) samples. In the only clinical trial reported on to date, Reinehr et al. (8) reported that children homozygous for the C-allele at SNP rs7566605 lost significantly less weight (P = 0.007) when engaged in a lifestyle-intervention program compared with children heterozygous or homozygous for the wild-type allele. These findings raise the possibility that the INSIG2 SNP may interact with lifestyle factors such as physical activity. This is an attractive possibility as it could help to explain why the reported associations between the INSIG2 rs7566605 genotype and obesity have varied across populations.

The SNP rs7566605 is located at 10 kb upstream of INSIG2 and has no known function. INSIG2 encodes a hijacking protein in the endoplasmic reticulum that, in response to changes in lipid levels, impedes the movement of sterol regulatory element binding proteins to the Golgi complex for processing and release to act as a nuclear transcription factor and regulator of lipid biosynthesis (9). Thus, individuals with altered INSIG2 activity may be at increased risk of obesity because of elevated triglycerides with subsequent storage in adipose tissues (10). Data from animal studies have suggested a role for INSIG2 in increasing triglyceride level in rats (11), as well as linkage to obesity phenotypes in mice (12). Cervino et al. (13) has also shown INSIG2 as a strong candidate susceptibility gene for total plasma cholesterol levels using a high-density SNP analysis in mice.

Herbert et al. (1) reported a difference of 1 BMI unit for the genotypes of the SNP rs7566605 in children under a recessive model and this difference tracked throughout life (11–60 years of age), suggesting that the SNP had an early onset effect on BMI. Hence, it is important to examine the effect of the INSIG2 genotypes on obesity during the early life when the impact of cumulative environmental factors on obesity predisposition may be less than in later life. Moreover, so far, there are only a few studies in children on the association of rs7566605 SNP with BMI (1,3,7,8). We, therefore, tested the association of rs7566605 SNP with obesity-related traits and lipids and examined for the interaction of the SNP with physical activity in the European Youth Heart Study (EYHS), a study of children and adolescents from Denmark and Estonia.

Subjects and Methods

  1. Top of page
  2. Abstract
  3. Subjects and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure
  8. REFERENCES

Study population

The details of the EYHS have been described in detail previously (14). Briefly, the EYHS is a school-based, cross-sectional study of pre- and early pubertal children randomly selected by a two-stage sampling strategy conducted in four countries: Denmark, Estonia, Norway, and Portugal.

Weight and height were measured using standard techniques with the participants in light clothing and barefoot. BMI was calculated as weight (kg)/height (m)2. BMI was standardized according to BMI reference charts derived by Cole's LMS method (15). This method summarizes the data in terms of three smooth age specific curves termed L (lambda), M (mu), and S (sigma). The M and S curves correspond to the median and coefficient of BMI variation at each age and gender, whereas the L curve allows for the substantial age dependent skewness in the distribution of BMI (15). WC (cm) was measured with a metal anthropometric tape midway between the lower rib margin and the iliac crest, at the end of gentle expiration. The measurements were taken twice, and the mean of the two values was used for further calculations. Four skinfold thickness measurements (triceps, biceps, subscapula, and suprailiac; mm) were taken on the left side of the body in duplicate or triplicate, according to the criteria described by Lohman et al. (16), and the two closest measurements at each site were averaged. Sexual maturity was assessed using the five-stage scale for breast development in girls and pubic hair in boys, according to Tanner (17).

Overnight fasting blood samples were taken in the morning from the antecubital vein. Samples were divided into aliquots, separated within 30 min and stored at −80 °C until transport to World Health Organization–certified laboratories for analyses. High-density lipoprotein cholesterol and triacylglycerol were measured by enzymatic methods in all samples (Olympus Diagnostica, Hamburg, Germany).

In the present study, a total of 930 boys and 1,073 girls from Danish and Estonian population were included. These boys and girls were recruited into two age groups: children (school grade 3) (mean age: 9.6 ± 0.4 years; range: 8.4–11.3 years) and adolescents (school grade 9) (mean age: 15.5 ± 0.5 years; range: 14.1–17.8 years).

Physical activity was assessed with an MTI Actigraph (Manufacturing Technology, Fort Walton Beach, FL) accelerometer over two weekdays and two weekend days (18,19,20,21). The outcome variable was daily activity (cpm), which is an indicator of the total amount (average intensity) of physical activity. This variable was derived by dividing total accelerometer counts per day by the duration the accelerometer was worn on each day, and then averaging across the measurement days. This variable has been shown to be significantly correlated with physical activity energy expenditure obtained by the doubly labelled water method (22). Before analyses, we excluded all time blocks with ≥10 consecutive zero counts, assuming that the monitor was not worn. We thereafter included children accumulating at least 600 min per day for at least 3 days including one weekend day. For the present study, physical-activity data were available only for 1,245 children.

The study was approved by the local scientific ethics committee and performed in accordance with the Helsinki Declaration. All parents gave written informed consent for their child to participate, and all children gave verbal consent.

Genotyping

Genotyping of the rs7566605 SNP was carried out using the TaqMan SNP Genotyping Assays (Applied Biosystems, Warrington, UK). The genotyping assays were undertaken on 10 ng of genomic DNA in a 5 µl 384-well TaqMan assay using a PTC-225 Thermal Cycler (MJ Research, Watertown, MA). The ABI PRISM 7900HT Sequence Detection System (Applied Biosystems, Warrington, UK) was used for end-point detection and allele calling. The call rate for genotyping was 98.9% and concordance of duplicates was 100%.

Statistical analysis

Statistical analyses were conducted using SAS 9.1 for Windows (SAS Institute, Cary, NC). A likelihood ratio test was performed to confirm that the observed genotype counts were in Hardy–Weinberg equilibrium (P = 0.09). The genotype distribution of Danish and Estonian children were significantly different (P = 0.03) and hence, association analyses are adjusted for country (Table 1). The association between the SNP and BMI was tested using generalized linear models assuming an additive effect for each additional minor allele. We also tested the recessive effect of the SNP on BMI, consistent with the observations by Herbert et al. (1). Interactions between SNP and age-group, gender, or country were also tested by including the appropriate interaction terms in the model. All models were adjusted for age, age-group, gender, sexual maturity, and country. The associations between SNP and WC and SNP and sum of four skinfolds were alone adjusted for height in addition to age, age-group, gender, sexual maturity, and country. Where lipid traits were the focus of the analyses, we also adjusted for analysis time to account for possible differences in laboratory procedures between countries. Obesity (n = 104) and overweight (n = 307) were defined as BMI above the 95th and 85th percentiles, respectively, for European children (23). WC and the sum of four skinfolds were log-transformed to obtain normal distribution for analyses; thus, geometric means are reported in the tables. Power calculations were performed using Quanto v1.1.1 (http:hydra.usc.edugxe) for a sample size of 2,003 individuals. The statistical power to detect a difference of 1 BMI unit as reported by Herbert et al. (1) under recessive model at a significance level of 1% was 98%.

Table 1.  Genotype counts and allele frequencies of the rs7566605 single-nucleotide polymorphism in the samples from Denmark and Estonia
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Results

  1. Top of page
  2. Abstract
  3. Subjects and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure
  8. REFERENCES

Table 2 shows the clinical and biochemical characteristics of the study population stratified by gender and age group. Genotype distributions by country are shown in Table 1.

Table 2.  Characteristics of the study participants stratified by gender and age-group
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Despite sufficient power, there was no significant association between rs7566605 SNP and BMI (recessive model, P = 0.24) (Table 3). Also using an additive model, we did not find any statistical difference in BMI (P = 0.68) between the genotype groups (Table 3). In addition, we did not find association of the rs7566605 SNP with WC (recessive, P = 0.12; additive, P = 0.68) and sum of four skinfolds (recessive P = 0.35; additive P = 0.39) (Table 3). Accordingly, we found no association with the risk of being overweight (P = 0.87) or obese (P = 0.34). Furthermore, we found no evidence of association between the rs7566605 SNP and any of the lipid traits (Table 3).

Table 3.  Characteristics of the study participants stratified by the genotypes of the single-nucleotide polymorphism rs7566605
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Rosskopf et al. (5) found that the effect of the rs7566605 SNP on BMI was stronger in overweight individuals. However, we did not find evidence of association of rs7566605 with BMI (Recessive: Overweight, P = 0.11, Obese, P = 0.66; Additive: Overweight, P = 0.30, Obese, P = 0.83).

There was no evidence of gender-specific effects (genotype-by-gender interaction: P = 0.55), age-group-specific effects (genotype-by-age-group interaction: P = 0.63) or country-specific effects (genotype-by-country interaction: P = 0.56). We also examined whether the association between the rs7566605 SNP and obesity-related traits was modified by physical-activity level, but found no evidence for significant interaction (recessive, β ± s.e. = 0.00021 ± 0.0004, P = 0.62; additive, β ± s.e. = 0.00001 ± 0.0002, P = 0.95).

Discussion

  1. Top of page
  2. Abstract
  3. Subjects and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure
  8. REFERENCES

Despite sufficient power to detect effect sizes reported previously (1), we found no evidence to suggest that the rs7566605 SNP at the INSIG2 gene is associated with traits for obesity or dyslipidemia in children from the EYHS. Thus, we failed to confirm the findings reported in the original study of US children (1). Our findings are however consistent with those of Dina et al. (3), who were also unable to confirm an association between the rs7566605 SNP and obesity in children. These observations are also consistent with other studies showing a lack of association of rs7566605 SNP with obesity in adults (4,24,25,26,27). In addition, we did not find association between the SNP and BMI among overweight and obese group, which is consistent with the recent report by Andreasen et al. (28).

Based on the hypothesis that alteration of INSIG2 activity can lead to obesity by the raising of triglycerides and subsequent storage in adipose tissue, we extended our analyses to examine the association of the rs7566605 SNP with total cholesterol, serum triglycerides, high-density and low-density lipoprotein levels. However, as with the obesity traits, we found no evidence of association between the rs7566605 SNP and lipid phenotypes. This finding is consistent with the studies of Smith et al. (24), Boes et al. (26), and Feng et al. (6), who observed no evidence of association between the rs7566605 SNP and lipid-related traits across different ethnic groups.

Recently (8), it was reported that children carrying the CC genotype at the rs7566605 SNP lost less weight compared with children with the GG- or GC-genotypes in a lifestyle-intervention program involving physical activity, nutrition, education, and behavior therapy. Hence, we investigated whether the association between the SNP and obesity-related traits was modified by physical-activity level. However, we found no evidence to support the notion that the effects of the rs7566605 SNP on obesity is modified by physical-activity levels in children from the EYHS. Andreasen et al. (28) showed an interaction between the rs7566605 SNP and the level of self-reported physical activity (P = 0.004) in 18,014 adult Danes. They observed a BMI difference of 0.53 (s.e. 0.42) kg/m2 when comparing physically passive homozygous C-allele carriers with physically passive G-allele carriers. Given the fact that our study was done in children and adolescents, this may account for the differences in the activity-related energy expenditure in children and adults.

We also examined whether the associations between the rs7566605 SNP and obesity-related phenotypes were modified by age, sex, or ethnicity. Again, there was no evidence that these factors modified the effects of the INSIG2 SNP in EYHS. It is however possible that other unmeasured factors modify the effects of the INSIG2 rs7566605 genotype on obesity-related traits in the EYHS.

One of the reasons for the absence of association between the rs7566605 SNP and obesity could be that differences in lifestyle factors such as diet overshadow the genetic association. This remains a possibility as interaction of the SNP with diet was not examined in the present study. We also cannot rule out the fact that our sample differs genetically and/or environmentally from the population studied by Herbert et al. (1). However, our failure to replicate the association of the rs7566605 SNP with BMI in a population-based sample of children and adolescents despite having sufficient power implicates the importance of independent studies in clarifying previously reported genetic associations. Moreover, the present study examined the effect of the SNP on obesity during the early stages of life, when environmental and behavioral factors have had less time to substantially modify the phenotype and hence, this study on children and adolescents gains importance.

In summary, the findings from our study points out that the rs7566605 SNP has no effect on obesity and its related traits in children and adolescents from Denmark and Estonia.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Subjects and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure
  8. REFERENCES

We are grateful to the volunteers in the EYHS, who gave their time to take part in this study. We also acknowledge the EYHS study teams for help with data collection. We thank Larissa Richardson for her assistance in genotyping. This study was supported by the following grants: The Danish Heart Foundation, The Danish Medical Research Council Health Foundation, The Danish Council for Sports Research, The Foundation in Memory of Asta Florida Bolding Renée Andersen, The Faculty of Health Sciences, University of Southern Denmark, The Estonian Science Foundation grant numbers 3277 and 5209; P.W.F was supported in part via grants from Novo Nordisk (370579201) and the Swedish Diabetes Association (DIA2006–013).

REFERENCES

  1. Top of page
  2. Abstract
  3. Subjects and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Disclosure
  8. REFERENCES
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