Novel Approaches in Psychiatric Genomics

Abstract

A central challenge in biomedical research remains identification of genetic factors influencing human behavior and susceptibility to common disease. Recent advances in genotyping technologies, coupled with the fundamental information provided by the Human Genome and International HapMap Projects, permit characterization and analysis of high-density SNP genotype data for thousands of individuals. Using genotype data obtained on the Illumina HumanHap550 SNP platform, for  1000 individuals (in  170 autism multiplex families from Autism Genetic Resource Exchange, 120 HapMap samples and 320 neurologically normal children from Children’s Hospital of Philadelphia) we performed a pilot study to identify genetics risk factors for autism susceptibility. Using these data we illustrate that novel statistical and computational biology approaches provide additional insights than can not be observed when using simple association tests. These novel approaches include: a) phylogenetic analysis of population structure; b) pathway-based analysis of genome-wide association data c) selection of variants based on a priori potential to affect phenotypes and d) analysis of copy number variation (CNVs) in autistic and healthy (control) children. In addition, our results demonstrate that high-density SNP genotyping array can be used to detect copy number variants (CNV) at an unprecedentedly high resolution and that regions with a high density of CNVs in many cases correspond to syntenic breakpoints, providing further support for the importance of evolutionary analysis of structural variation to disease and disease susceptibility.

This is a joint work with Junhyong Kim (Penn), Mingyao Li (Penn) and Hakon Hakonarson (CHOP).