Institute of Human Genetics, University of Bonn, Bonn, Germany.
PLoS One. 2013 Jul 2;8(7):e64035. doi: 10.1371/journal.pone.0064035. Print 2013.
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.
大片段罕见拷贝数变异(CNVs)已被认为是精神分裂症(SCZ)发生的重要遗传风险因素。然而,由于其在患者中的频率较低(1∶150 至 1∶1000),需要大样本量才能检测到特定 CNVs 与 SCZ 之间的关联。到目前为止,大多数全基因组 CNV 分析主要集中在报告仅在研究队列中达到显著 P 值的 CNVs,并且仅确认了已建立的风险携带 CNVs 的频率。因此,与 SCZ 易感性相关的低频 CNVs 可能会在二次分析中丢失。在这项研究中,我们提供了一个简洁的高质量 CNV 集合,该集合来自一个由 1637 名 SCZ 或分裂情感障碍患者和 1627 名对照组成的大型德国样本。所有个体均在 Illumina 的 BeadChips 上进行基因分型,并使用 QuantiSNP 和 PennCNV 识别潜在的 CNVs。只有被两个程序检测到且跨越≥30 个连续 SNP 的 CNVs 才被包含在数据收集和下游分析中(2366 个 CNVs,每个个体 0.73 个 CNVs)。全基因组分析并未揭示出一个以前未知的 CNV 与 SCZ 之间的特定关联。然而,以前报道与 SCZ 相关的 CNV 组在我们的患者中比在对照组中更为常见。我们数据集的发布将成为其他研究小组独特、易于访问、高质量的 CNV 数据集。该数据集可用于识别新的与疾病相关的 CNVs,由于其极低的频率和单个研究中检测它们的能力不足,这些 CNVs 目前被忽视。