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

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.

Association of gene coding variation and resting metabolic rate in a multi-ethnic sample of children and adults

“…One SNP in this gene was nominally associated with RMR in the present study, although not reaching robust statistical significance thresholds ( p -value = 3.0 × 10 −4 ). Other genes in this region have also been implicated in differential adipose deposition ( LARGE [78] and HMGXB4 [34]) and fat mass (near ODF3B ) [25], and electronic medical record-defined BMI in children ( APOL5 ) [79], suggesting that our study has detected a biological relationship with energy balance or storage in this region, consistent with these previous studies.…”

Energy homeostasis genes and breast cancer risk: The influence of ancestry, body size, and menopausal status, the breast cancer health disparities study

“…CCK is a satiety hormone and has been associated with obesity. CCK rs8192472 specifically has been reported as being associated with obesity and was identified as a predictor of obesity in GWAS [29]. We found that CCK rs8192472 was marginally associated with breast cancer risk among women with high IA ancestry after adjustment for multiple comparisons (data not shown, OR = 0.55, 95% CI 0.33–0.91; p = 0.02 and p adj 0.059).…”

Identifying Genetic Associations With Variability in Metabolic Health and Blood Count Laboratory Values: Diving Into the Quantitative Traits by Leveraging Longitudinal Data From an Ehr

“…Thus, integrating both clinical laboratory measurements and diagnosis codes present powerful approaches for understanding genetic variants that show similar associations with both data types obtained from an EHR 3 . The majority of association studies that use quantitative traits derived from an EHR as phenotypes use either mean/median values 3,6 or most recent measurements 7 . While this approach has been successful, utilizing only mean/median values limits the understanding of these traits by neglecting the variability over time that may be present in an individual patient's clinical history.…”