title: On the association of common and rare genetic variation influencing body mass index: a combined SNP and CNV analysis.
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)).
  
  
  CONCLUSIONS
  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.
authors.affiliation: Virginia Institute for Psychiatric and Behavioral Genetics, Department of Human and Molecular Genetics, School of Medicine, Virginia Commonwealth University, Biotech I, 800 E, Leigh Street, Richmond, VA 23298-0126, USA. repeterson@vcu.edu.
authors.forename: Roseann E
authors.initials: RE
authors.lastname: Peterson
authors.forename: Hermine H
authors.initials: HH
authors.lastname: Maes
authors.forename: Peng
authors.initials: P
authors.lastname: Lin
authors.forename: John R
authors.initials: JR
authors.lastname: Kramer
authors.forename: Victor M
authors.initials: VM
authors.lastname: Hesselbrock
authors.forename: Lance O
authors.initials: LO
authors.lastname: Bauer
authors.forename: John I
authors.initials: JI
authors.lastname: Nurnberger
authors.forename: Howard J
authors.initials: HJ
authors.lastname: Edenberg
authors.forename: Danielle M
authors.initials: DM
authors.lastname: Dick
authors.forename: Bradley T
authors.initials: BT
authors.lastname: Webb
mesh_terms: D019540:Area Under Curve; D015992:Body Mass Index; D056915:DNA Copy Number Variations; D014644:Genetic Variation; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D009765:Obesity / Q000235:genetics / Q000473:pathology; D016017:Odds Ratio; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D012372:ROC Curve