Genomewide Copy Number Variation Analysis and Association with Facial Shape Variation

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 DESCRIPTION (provided by applicant): Family-based studies have indicated that genetic factors play a significant role in facial shape and appearance. However, very little is known about the genes that underlie normal facial development and account for inter-individual variability. In two ongoing studies to identify the genetic determinants underlying facial shape variation, 3700 Bantu Africans and 3200 European-derived Caucasians (EUR) were photographed using 3D morphometric cameras to obtain digitized facial scans and genotyped using high-content genotyping microarrays. The precise facial measurements obtained from 3D facial scans, allowed the extraction of quantitative facial distances and shapes which account for the majority of facial shape variance among study subjects. Genome-wide association of single nucleotide polymorphisms (SNPs) with the quantitative facial measurements in these African and European cohorts, are currently ongoing. In addition to SNPs, copy number variations (CNVs) are now recognized as a significant source of genetic variation underlying human variability and disease. Recent studies have led to the association of CNVs to increased risk for several of common diseases, most notably neurodevelopmental diseases like autism and schizophrenia. Furthermore, CNVs have been directly implicated in several genetic disorders such as the 22q11 deletion syndrome and Williams-Beuren syndrome, in which the affected individuals have characteristic facial dysmorphia. We hypothesize that some of the variability in normal facial shape and appearance results from genetic variation mediated by the copy number variation affecting the dosage of genes involved in facial development. To test our hypothesis, we will first carry out a CNV analysis using the existing data from the SNP microarrays used to genotype the Bantu African and EUR cohorts. We will then carry out association analysis of the detected CNVs with the quantitative facial measurements in a multistep approach, which will test for the association of both common and rare variants. The proposed analysis will directly assess the contribution of CNVs in the genetics of facial shape and appearance. Furthermore, the identification of specific genes affected by these CNVs will greatly expand our understanding of the genetic and developmental pathways underlying normal facial morphogenesis as well as craniofacial abnormalities.