Affiliations: Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
Note:  Corresponding author: Hakon Hakonarson, Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104 – 4318, USA. Tel.: +1 267 426 0088; Fax: +1 267 426 0363; E-mail: [email protected]
Abstract: Previous large-scale genome-wide association studies in adult populations have implicated ~100 loci in determining high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, or triglyceride levels. However, whether these loci also contribute to variations of lipid traits in pediatric populations remain unknown. Here we assayed a population of Philadelphia children by high-density single nucleotide polymorphism arrays, and performed association analysis on lipid traits ascertained from lipid measurements stored in electronic medical records. We examined previously reported lipid trait associations, and found that most of them show identical direction of association in our pediatric cohorts, including genome-wide significant association on cholesteryl ester transfer protein with HDL-C levels (rs3764261, P = 2.1 × 10−8) and other significant associations on oxysterol-binding protein-like protein 7, low-density lipoprotein receptor-related protein 4 and low-density lipoprotein receptor-related protein 1. Additionally, we identified suggestive association on low-density lipoprotein receptor-related protein 1B with HDL-C levels (rs17736712, P = 2.1 × 10−7), but this signal is not supported by previous meta-analysis on adult cohorts. Finally, we examined rare copy number variants and identified deletions encompassing tetratricopeptide repeat domain 39B in two children with extreme lipid measures. Our results highlight the commonalities and differences of genetic components in determining lipid traits in pediatric versus adult populations. Furthermore, our study demonstrates the unique utility of automated information retrieval from electronic medical records in facilitating the identification of genotype-phenotype associations.