In the past 3 years, 13 genetic loci have been implicated for BMI from the outcomes of genome-wide association (GWA) studies primarily in adults. Insulin-induced gene 2 (INSIG2) was the first locus to be reported by this method to have a role in obesity (1) but replication attempts have yielded inconsistent outcomes (2,3,4,5,6). The second reported locus, the fat mass- and obesity-associated gene (FTO) (7), has been more robustly observed by others (8,9,10,11). Subsequent larger studies have uncovered 11 additional genes (12,13,14), first melanocortin 4 receptor (MC4R) from a multicenter meta-analysis (12), then the GIANT consortium revealed six more genes (transmembrane protein 18 (TMEM18), potassium channel tetramerization domain containing 15 (KCTD15), glucosamine-6-phosphate deaminase 2 (GNPDA2), SH2B adaptor protein 1 (SH2B1), mitochondrial carrier 2 (MTCH2), and neuronal growth regulator 1 (NEGR1)) (14), five of which were confirmed in the GWA study reported from Iceland (but not GNPDA2 due to an unavailable proxy single-nucleotide polymorphism (SNP)), who also uncovered and reported loci on 1q25, 3q27, and 12q13 (ref. 13) and verified association with the brain-derived neurotrophic factor (BDNF) gene (15).
In this study, we aimed at examining these findings in a large pediatric cohort with BMI measures and to determine the relative impact of these variants in childhood. For this purpose, we leveraged genotyping data from our ongoing GWA study of BMI variation in children. The 25 SNPs corresponding to the 13 previously reported obesity loci were investigated with respect to their association to normalized pediatric BMI (Table 1; also Supplementary Table S1 for analyses by age categories).
In summary, 15 of these SNPs yielded at least nominally significant association to BMI (P < 0.05), representing nine different loci with the same direction of effect as previously reported. Of these nine loci, variants at the FTO locus yielded the strongest association with P < 10−4, namely rs8044769 and rs3751812 (P = 7.26 × 10−5 and 9.68 × 10−5, respectively); in addition, this locus also yielded association with rs8050136 and rs7190492 (P = 1.40 × 10−4 and 0.021, respectively) but not with rs6499640.
With a similar magnitude of association to FTO was TMEM18, with rs2867125 yielding a P = 9.72 × 10−5, together with almost as strongly associated SNPs, rs7561317 and rs4854344 (P = 1.02 × 10−4 and 1.52 × 10−4, respectively). Indeed, it is interesting to note that the two adult cohorts that uncovered TMEM18 in obesity also showed it to be second only in significance to FTO (13,14). The third most significantly associated locus was at GNPDA2, (rs13130484; P = 1.32 × 10−4).
Overall, in addition to FTO, TMEM18, and GNPDA2, we found evidence for association at the INSIG2, MC4R, NEGR1, 1q25, BDNF, and KCTD15 loci. One could argue that we have carried out multiple testing in our BMI cohort for these previously reported SNPs, albeit at a number of magnitudes less than for a full GWA study. If we were to apply the strictest correction, i.e., the Bonferroni correction based on 25 SNPs, then FTO, TMEM18, GNPDA2, and MC4R would still be considered significant. This is very much in line with the observations made with the pediatric cohort utilized by Willer et al. (14); however the one exception is that we do not observe strong association with KCTD15.
It was also observed that SNPs residing at the 12q13, 3q27, MTCH2, and SH2B1 loci did not reveal any evidence of association with BMI in our pediatric cohort.
The positive results for FTO and MC4R come as no surprise as we have previously reported their association with the Centers for Disease Control and Prevention–defined 95th percentile of BMI, i.e., obesity, in our pediatric cohort, but limited to ages 2–18 years old (8,16). In this study, where we utilized BMI z-score on all children 0–18 years old, it is satisfying that they continue to show association at a similar magnitude.
One of the more notable results is the positive association with INSIG2. This association with pediatric BMI, albeit at just the nominal level, will further add to the debate on the relevance of INSIG2 in BMI determination.
For the loci we did not observe any evidence for association for at all may be due to power issues, but could also indicate that they have a less pronounced role in a pediatric setting. Indeed, many of the newly uncovered genes have been implicated in neurological functions, genes which may be more important in BMI determination in adults rather than in children, where other more direct metabolic genes could play a more important role.
Finally, we investigated the 15 significant SNPs further by testing for association between BMI z-score and the genotype score by summing the number of BMI increasing alleles across all these SNPs. The resulting P value for the genotype score was 2.53 × 10−16 (Figure 1). The genotype score explains 1.12% of the total variation for BMI z-score. We also tested pair-wise interactions between the 15 significant SNPs, but none of the interaction effects were significant (Supplementary Table S2), suggesting that these 15 SNPs act additively on the pediatric BMI z-score. As such, we did observe a cumulative effect but not as striking as reported by the GIANT consortium in their adult cohorts (14).
From this analysis, it is clear that a number of loci previously reported from GWA analyses of adult BMI and/or obesity also play a role in our phenotype of interest. Although these recently discovered loci unveil several new biomolecular pathways not previously associated with obesity, it is important to note that these well-established genetic associations with obesity explain very little of the genetic risk for this pediatric phenotype, suggesting the existence of additional loci whose number and effect size remain unknown. Once our GWA study is complete, we will have the opportunity to look for other variants in the genome that are associated with BMI in childhood.