On the association of common and rare genetic variation influencing body mass index: A combined SNP and CNV analysis

Roseann E. Peterson, Hermine H. Maes, Peng Lin, John R. Kramer, Victor M. Hesselbrock, Lance O. Bauer, John I. Nurnberger, Howard J. Edenberg, Danielle M. Dick, Bradley T. Webb

Research output: Contribution to journalArticle

16 Scopus citations

Abstract

Background: As the architecture of complex traits incorporates a widening spectrum of genetic variation, analyses integrating common and rare variation are needed. Body mass index (BMI) represents a model trait, since common variation shows robust association but accounts for a fraction of the heritability. A combined analysis of single nucleotide polymorphisms (SNP) and copy number variation (CNV) was performed using 1850 European and 498 African-Americans from the Study of Addiction: Genetics and Environment. Genetic risk sum scores (GRSS) were constructed using 32 BMI-validated SNPs and aggregate-risk methods were compared: count versus weighted and proxy versus imputation.Results: The weighted SNP-GRSS constructed from imputed probabilities of risk alleles performed best and was highly associated with BMI (p = 4.3×10-16) accounting for 3% of the phenotypic variance. In addition to BMI-validated SNPs, common and rare BMI/obesity-associated CNVs were identified from the literature. Of the 84 CNVs previously reported, only 21-kilobase deletions on 16p12.3 showed evidence for association with BMI (p = 0.003, frequency = 16.9%), with two CNVs nominally associated with class II obesity, 1p36.1 duplications (OR = 3.1, p = 0.009, frequency 1.2%) and 5q13.2 deletions (OR = 1.5, p = 0.048, frequency 7.7%). All other CNVs, individually and in aggregate, were not associated with BMI or obesity. The combined model, including covariates, SNP-GRSS, and 16p12.3 deletion accounted for 11.5% of phenotypic variance in BMI (3.2% from genetic effects). Models significantly predicted obesity classification with maximum discriminative ability for morbid-obesity (p = 3.15×10-18).Conclusion: Results show that incorporating validated effect sizes and allelic probabilities improve prediction algorithms. Although rare-CNVs did not account for significant phenotypic variation, results provide a framework for integrated analyses.

Original languageEnglish (US)
Article number368
JournalBMC genomics
Volume15
Issue number1
DOIs
StatePublished - May 14 2014

Keywords

  • Body mass index
  • Copy number variation
  • FTO
  • Genome-wide association
  • MC4R
  • Obesity
  • Polygenic score
  • Risk prediction

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Medicine(all)

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    Peterson, R. E., Maes, H. H., Lin, P., Kramer, J. R., Hesselbrock, V. M., Bauer, L. O., Nurnberger, J. I., Edenberg, H. J., Dick, D. M., & Webb, B. T. (2014). On the association of common and rare genetic variation influencing body mass index: A combined SNP and CNV analysis. BMC genomics, 15(1), [368]. https://doi.org/10.1186/1471-2164-15-368