Whole genome analysis of copy number variation in a case control study of recurrent depressive disorder

Rare copy number variants (CNV), defined as deletions and duplications of genetic material over 1,000 base pairs in length, have become the focus of considerable interest in psychiatric disorders, where a proportion of individuals harbour rare and de novo events not usually seen in controls. We have...

Full description

Bibliographic Details
Main Author: Rucker, James
Published: King's College London (University of London) 2012
Subjects:
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.628137
Description
Summary:Rare copy number variants (CNV), defined as deletions and duplications of genetic material over 1,000 base pairs in length, have become the focus of considerable interest in psychiatric disorders, where a proportion of individuals harbour rare and de novo events not usually seen in controls. We have performed a genome wide association study of copy number variation in 3,106 cases of recurrent depressive disorder, 1,731 controls screened for a lifetime absence of psychiatric disorder, and 5,619 population controls from phase 2 of the Wellcome Trust Case Control Consortium. Analysing our data with the PennCNV method, we found an enrichment of rare deletion CNVs in our case cohort, especially when compared to our screened control cohort. This finding was supported by further analysis with the iPattern method, but not by the QuantiSNP method. We followed up a selection of cases and controls with a comparative genomic hybridisation (CGH) array focussed on the region 22qll.2, which is a neuro-gene rich region of the human genome under current active evolutionary selection and resident to a deletion syndrome which commonly manifests with psychiatric disorders. We found no significant differences in CNV burden between our case and control cohorts. Finally we ran association analyses with our CNV call sets, including a high quality intersected call set derived from all three methods, against various phenotypes obtained from a combined database of all studies that contributed samples to this GWAS. We found no associations that survived Bonferroni correction for multiple testing.