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Front Genet. 2013 Dec 3;4:268. doi: 10.3389/fgene.2013.00268. eCollection 2013.

EMR-linked GWAS study: investigation of variation landscape of loci for body mass index in children.

Author information

1
Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA.
2
Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; School of Medicine, University of Cincinnati Cincinnati, OH, USA.
3
School of Medicine, University of Cincinnati Cincinnati, OH, USA ; Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA.
4
Division of Genetics and Genomics, Boston Children's Hospital Boston, MA, USA.
5
Division of Genetics and Genomics, Department of Pediatrics, The Manton Center for Orphan Disease Research, Boston Children's Hospital, Harvard Medical School Boston, MA, USA.
6
National Human Genome Research Institute, National Institutes of Health Bethesda, MD, USA.
7
Center for Biomedical Informatics, Harvard Medical School and Children's Hospital Informatics Program Boston, MA, USA.
8
Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; School of Medicine, University of Cincinnati Cincinnati, OH, USA ; Department of Veteran Affairs Medical Center Cincinnati, OH, USA.

Abstract

Common variations at the loci harboring the fat mass and obesity gene (FTO), MC4R, and TMEM18 are consistently reported as being associated with obesity and body mass index (BMI) especially in adult population. In order to confirm this effect in pediatric population five European ancestry cohorts from pediatric eMERGE-II network (CCHMC-BCH) were evaluated.

METHOD:

Data on 5049 samples of European ancestry were obtained from the Electronic Medical Records (EMRs) of two large academic centers in five different genotyped cohorts. For all available samples, gender, age, height, and weight were collected and BMI was calculated. To account for age and sex differences in BMI, BMI z-scores were generated using 2000 Centers of Disease Control and Prevention (CDC) growth charts. A Genome-wide association study (GWAS) was performed with BMI z-score. After removing missing data and outliers based on principal components (PC) analyses, 2860 samples were used for the GWAS study. The association between each single nucleotide polymorphism (SNP) and BMI was tested using linear regression adjusting for age, gender, and PC by cohort. The effects of SNPs were modeled assuming additive, recessive, and dominant effects of the minor allele. Meta-analysis was conducted using a weighted z-score approach.

RESULTS:

The mean age of subjects was 9.8 years (range 2-19). The proportion of male subjects was 56%. In these cohorts, 14% of samples had a BMI ≥95 and 28 ≥ 85%. Meta analyses produced a signal at 16q12 genomic region with the best result of p = 1.43 × 10(-) (7) [p (rec) = 7.34 × 10(-) (8)) for the SNP rs8050136 at the first intron of FTO gene (z = 5.26) and with no heterogeneity between cohorts (p = 0.77). Under a recessive model, another published SNP at this locus, rs1421085, generates the best result [z = 5.782, p (rec) = 8.21 × 10(-) (9)]. Imputation in this region using dense 1000-Genome and Hapmap CEU samples revealed 71 SNPs with p < 10(-) (6), all at the first intron of FTO locus. When hetero-geneity was permitted between cohorts, signals were also obtained in other previously identified loci, including MC4R (rs12964056, p = 6.87 × 10(-) (7), z = -4.98), cholecystokinin CCK (rs8192472, p = 1.33 × 10(-) (6), z = -4.85), Interleukin 15 (rs2099884, p = 1.27 × 10(-) (5), z = 4.34), low density lipoprotein receptor-related protein 1B [LRP1B (rs7583748, p = 0.00013, z = -3.81)] and near transmembrane protein 18 (TMEM18) (rs7561317, p = 0.001, z = -3.17). We also detected a novel locus at chromosome 3 at COL6A5 [best SNP = rs1542829, minor allele frequency (MAF) of 5% p = 4.35 × 10(-) (9), z = 5.89].

CONCLUSION:

An EMR linked cohort study demonstrates that the BMI-Z measurements can be successfully extracted and linked to genomic data with meaningful confirmatory results. We verified the high prevalence of childhood rate of overweight and obesity in our cohort (28%). In addition, our data indicate that genetic variants in the first intron of FTO, a known adult genetic risk factor for BMI, are also robustly associated with BMI in pediatric population.

KEYWORDS:

BMI; GWAS; obesity; polymorphism

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