Copy Number Variants in German Patients with Schizophrenia

Lutz Priebe,Heinrich Sauer,Rebecca Kulbida,Manuel Mattheisen,Henrik Walter,Markus M Nöthen,Dan Rujescu,René Breuer,Per Hoffmann,Stefan Herms,Stephanie H Witt,Marcella Rietschel,Sven Cichon,Susanne Moebus,Franziska Degenhardt,Jana Strohmaier,Wolfgang Maier,Andreas Meyer‐Lindenberg ,Rainald Mößner ,Igor Nenadić

doi:10.1371/journal.pone.0064035

Abstract

Large rare copy number variants (CNVs) have been recognized as significant genetic risk factors for the development of schizophrenia (SCZ). However, due to their low frequency (1∶150 to 1∶1000) among patients, large sample sizes are needed to detect an association between specific CNVs and SCZ. So far, the majority of genome-wide CNV analyses have focused on reporting only CNVs that reached a significant P-value within the study cohort and merely confirmed the frequency of already-established risk-carrying CNVs. As a result, CNVs with a very low frequency that might be relevant for SCZ susceptibility are lost for secondary analyses. In this study, we provide a concise collection of high-quality CNVs in a large German sample consisting of 1,637 patients with SCZ or schizoaffective disorder and 1,627 controls. All individuals were genotyped on Illumina's BeadChips and putative CNVs were identified using QuantiSNP and PennCNV. Only those CNVs that were detected by both programs and spanned ≥30 consecutive SNPs were included in the data collection and downstream analyses (2,366 CNVs, 0.73 CNVs per individual). The genome-wide analysis did not reveal a specific association between a previously unknown CNV and SCZ. However, the group of CNVs previously reported to be associated with SCZ was more frequent in our patients than in the controls. The publication of our dataset will serve as a unique, easily accessible, high-quality CNV data collection for other research groups. The dataset could be useful for the identification of new disease-relevant CNVs that are currently overlooked due to their very low frequency and lack of power for their detection in individual studies.

Highlights

Schizophrenia (SCZ) is a severe and debilitating neuropsychiatric disorder with a lifetime prevalence of 0.5–1%
Genome-wide association analysis We performed a genome-wide analysis to uncover associations between specific copy number variants (CNVs) and SCZ, but we did not detect any specific CNVs to be nominally significantly associated with the disorder
We provide a unique, high-quality CNV data collection in a clinically well characterized sample of 1,637 patients with SCZ and schizoaffective disorder (SCZA)

Summary

Introduction

Schizophrenia (SCZ) is a severe and debilitating neuropsychiatric disorder with a lifetime prevalence of 0.5–1%. Several large copy number variants (CNVs) have been identified as risk factors for SCZ susceptibility [2,3,4,5,6,7,8,9,10,11,12,13,14]. SCZ, the frequency of such CNVs is low and ranges between 1:150 and 1:1,000 [15]. We set out to compile a concise collection of high-quality CNV calls in a clinically well-characterized sample of 1,637 patients with SCZ or schizoaffective disorder (SCZA). Using data from 1,627 controls we (i) performed a genomewide CNV analysis, and (ii) checked the frequency of CNVs previously reported to be associated with schizophrenia

Methods

Results

Conclusion