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Genetic susceptibility to obesity and related traits in childhood and adolescence: influence of loci identified by genome-wide association studies.

den Hoed M, Ekelund U, Brage S, Grontved A, Zhao JH, Sharp SJ, Ong KK, Wareham NJ, Loos RJ - Diabetes (2010)

Bottom Line: The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 × 10(-11)).Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 × 10(-5)), 0.039 SD, in sum of skinfolds (P = 1.7 × 10(-7)), and 0.022 SD in waist circumference (P = 1.7 × 10(-4)), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference).Whereas the association of some variants may differ with age, the cumulative effect size is similar.

View Article: PubMed Central - PubMed

Affiliation: Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Cambridge, UK.

ABSTRACT

Objective: Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents.

Research design and methods: Seventeen variants representing 16 obesity susceptibility loci were genotyped in 1,252 children (mean ± SD age 9.7 ± 0.4 years) and 790 adolescents (15.5 ± 0.5 years) from the European Youth Heart Study (EYHS). We tested for association of individual variants and a genetic predisposition score (GPS-17), calculated by summing the number of effect alleles, with anthropometric traits. For 13 variants, summary statistics for associations with BMI were meta-analyzed with previously reported data (N(total) = 13,071 children and adolescents).

Results: In EYHS, 15 variants showed associations or trends with anthropometric traits that were directionally consistent with earlier reports in adults. The meta-analysis showed directionally consistent associations with BMI for all 13 variants, of which 9 were significant (0.033-0.098 SD/allele; P < 0.05). The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 × 10(-11)). Effect sizes for BMI tended to be more pronounced in children and adolescents than reported earlier in adults for variants in or near SEC16B, TMEM18, and KCTD15, (0.028-0.035 SD/allele higher) and less pronounced for rs925946 in BDNF (0.028 SD/allele lower). Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 × 10(-5)), 0.039 SD, in sum of skinfolds (P = 1.7 × 10(-7)), and 0.022 SD in waist circumference (P = 1.7 × 10(-4)), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference).

Conclusions: Most obesity susceptibility loci identified by GWA studies in adults are already associated with anthropometric traits in children/adolescents. Whereas the association of some variants may differ with age, the cumulative effect size is similar.

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Association of variants in the obesity susceptibility loci with BMI after meta-analysis in a maximal sample of 13,071 (NEGR1, TMEM18, GNPDA2, MTCH2, SH2B1, FTO, MC4R, and KCTD15) or 8,120 (SEC16B, ETV5, BDNF, and BCIN3D) children and adolescents compared with 20,431 adults from the EPIC-Norfolk cohort. Effect sizes (B) and 95% CIs are shown; I2 and P values for heterogeneity between age-groups are additionally provided.
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Figure 3: Association of variants in the obesity susceptibility loci with BMI after meta-analysis in a maximal sample of 13,071 (NEGR1, TMEM18, GNPDA2, MTCH2, SH2B1, FTO, MC4R, and KCTD15) or 8,120 (SEC16B, ETV5, BDNF, and BCIN3D) children and adolescents compared with 20,431 adults from the EPIC-Norfolk cohort. Effect sizes (B) and 95% CIs are shown; I2 and P values for heterogeneity between age-groups are additionally provided.

Mentions: A genetic predisposition score (GPS) was calculated by summing the number of effect alleles carried by each individual (GPS-17). The GPS-17 was normally distributed, with the majority of individuals (73.8%) carrying 13–18 of the 34 possible effect alleles. Only 2.9% of the individuals carried 10 or fewer effect alleles, and 3.2% carried ≥21 (Fig. 1). We did not weight the effect alleles by their effect size, which has been suggested to have only a limited effect (40), to allow comparison with the nonweighted score reported for adults of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk study. The latter represents the largest population-based study (N = 20,431) thus far in which the association of variants in all 12 loci identified in GWA studies for BMI have been examined in a consistent manner and the only study that has additionally reported their cumulative association with BMI and waist circumference (39). Given its large sample size, effect sizes are likely stable and representative. An alternative GPS (GPS-12) was calculated in EYHS, which contained 12 variants representing the 12 loci discovered in GWA studies for BMI (Fig. 3) (39). Associations of GPS-17 and GPS-12 with continuous anthropometric traits and the risk of obesity and overweight were examined using general linear model and logistic regression analyses, respectively. Differences in effect size of the GPS-12 between children/adolescents and adults were examined by estimating the amount of heterogeneity between the two groups.


Genetic susceptibility to obesity and related traits in childhood and adolescence: influence of loci identified by genome-wide association studies.

den Hoed M, Ekelund U, Brage S, Grontved A, Zhao JH, Sharp SJ, Ong KK, Wareham NJ, Loos RJ - Diabetes (2010)

Association of variants in the obesity susceptibility loci with BMI after meta-analysis in a maximal sample of 13,071 (NEGR1, TMEM18, GNPDA2, MTCH2, SH2B1, FTO, MC4R, and KCTD15) or 8,120 (SEC16B, ETV5, BDNF, and BCIN3D) children and adolescents compared with 20,431 adults from the EPIC-Norfolk cohort. Effect sizes (B) and 95% CIs are shown; I2 and P values for heterogeneity between age-groups are additionally provided.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2963559&req=5

Figure 3: Association of variants in the obesity susceptibility loci with BMI after meta-analysis in a maximal sample of 13,071 (NEGR1, TMEM18, GNPDA2, MTCH2, SH2B1, FTO, MC4R, and KCTD15) or 8,120 (SEC16B, ETV5, BDNF, and BCIN3D) children and adolescents compared with 20,431 adults from the EPIC-Norfolk cohort. Effect sizes (B) and 95% CIs are shown; I2 and P values for heterogeneity between age-groups are additionally provided.
Mentions: A genetic predisposition score (GPS) was calculated by summing the number of effect alleles carried by each individual (GPS-17). The GPS-17 was normally distributed, with the majority of individuals (73.8%) carrying 13–18 of the 34 possible effect alleles. Only 2.9% of the individuals carried 10 or fewer effect alleles, and 3.2% carried ≥21 (Fig. 1). We did not weight the effect alleles by their effect size, which has been suggested to have only a limited effect (40), to allow comparison with the nonweighted score reported for adults of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk study. The latter represents the largest population-based study (N = 20,431) thus far in which the association of variants in all 12 loci identified in GWA studies for BMI have been examined in a consistent manner and the only study that has additionally reported their cumulative association with BMI and waist circumference (39). Given its large sample size, effect sizes are likely stable and representative. An alternative GPS (GPS-12) was calculated in EYHS, which contained 12 variants representing the 12 loci discovered in GWA studies for BMI (Fig. 3) (39). Associations of GPS-17 and GPS-12 with continuous anthropometric traits and the risk of obesity and overweight were examined using general linear model and logistic regression analyses, respectively. Differences in effect size of the GPS-12 between children/adolescents and adults were examined by estimating the amount of heterogeneity between the two groups.

Bottom Line: The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 × 10(-11)).Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 × 10(-5)), 0.039 SD, in sum of skinfolds (P = 1.7 × 10(-7)), and 0.022 SD in waist circumference (P = 1.7 × 10(-4)), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference).Whereas the association of some variants may differ with age, the cumulative effect size is similar.

View Article: PubMed Central - PubMed

Affiliation: Medical Research Council Epidemiology Unit, Institute of Metabolic Science, Cambridge, UK.

ABSTRACT

Objective: Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents.

Research design and methods: Seventeen variants representing 16 obesity susceptibility loci were genotyped in 1,252 children (mean ± SD age 9.7 ± 0.4 years) and 790 adolescents (15.5 ± 0.5 years) from the European Youth Heart Study (EYHS). We tested for association of individual variants and a genetic predisposition score (GPS-17), calculated by summing the number of effect alleles, with anthropometric traits. For 13 variants, summary statistics for associations with BMI were meta-analyzed with previously reported data (N(total) = 13,071 children and adolescents).

Results: In EYHS, 15 variants showed associations or trends with anthropometric traits that were directionally consistent with earlier reports in adults. The meta-analysis showed directionally consistent associations with BMI for all 13 variants, of which 9 were significant (0.033-0.098 SD/allele; P < 0.05). The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 × 10(-11)). Effect sizes for BMI tended to be more pronounced in children and adolescents than reported earlier in adults for variants in or near SEC16B, TMEM18, and KCTD15, (0.028-0.035 SD/allele higher) and less pronounced for rs925946 in BDNF (0.028 SD/allele lower). Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 × 10(-5)), 0.039 SD, in sum of skinfolds (P = 1.7 × 10(-7)), and 0.022 SD in waist circumference (P = 1.7 × 10(-4)), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference).

Conclusions: Most obesity susceptibility loci identified by GWA studies in adults are already associated with anthropometric traits in children/adolescents. Whereas the association of some variants may differ with age, the cumulative effect size is similar.

Show MeSH
Related in: MedlinePlus