拷贝数变异(CNV)是通过主要在高加索人群中进行的基因组规模研究在精神分裂症(SZ)中鉴定的主要遗传因素之一。然而,到目前为止,没有来自印度患者的基因组规模的CNV报告。为了解决这个缺点,我们产生了,第一次,来自印度南部的168名SZ患者和168名对照的基因组规模CNV数据。总的来说,在56名患者和46名对照中鉴定出63种不同的CNV,在患者中进行多次测试(FDR=2.7E-4)后,中等大小缺失(100kb-1Mb)的比例明显更高。其中,以前报告了13个CNV;然而,当针对GWAS进行搜索时,转录组,exome,和DNA甲基化研究,鉴定了另外17个具有候选基因的CNVs.在总共30个CNV中,38例患者中有28例,27例对照中有12例,表明前者的代表性明显更高(p=1.87E-5)。仅4q35.1-q35.2重复是显著的(p=0.020),并且在11个对照和2个患者中观察到。在其他不重要的方面,一些患者特异性和先前报道的CNV的例子包括11q14.1(DLG2)的缺失,22q11.21和14q21.1(LRFN5)。16p13.3删除(RBFOX1),3p14.2重复(CADPS),和7p11.2重复(CCT6A)是一些含有候选基因的新型CNV。然而,这些观察结果需要在更大的样本量中复制。总之,该报告为未来在相对未开发的人群中进行CNV研究奠定了重要基础.此外,数据表明,使用综合方法可以更好地识别SZ和其他心理健康障碍的候选CNV。
Copy number variants (
CNVs) are among the main genetic factors identified in schizophrenia (SZ) through genome-scale studies conducted mostly in Caucasian populations. However, to date, there have been no genome-scale CNV reports on patients from India. To address this shortcoming, we generated, for the first time, genome-scale CNV data for 168 SZ patients and 168 controls from South India. In total, 63 different
CNVs were identified in 56 patients and 46 controls with a significantly higher proportion of medium-sized deletions (100 kb-1 Mb) after multiple testing (FDR = 2.7E-4) in patients. Of these, 13
CNVs were previously reported; however, when searched against GWAS, transcriptome, exome, and DNA methylation studies, another 17
CNVs with candidate genes were identified. Of the total 30
CNVs, 28 were present in 38 patients and 12 in 27 controls, indicating a significantly higher representation in the former (p = 1.87E-5). Only 4q35.1-q35.2 duplications were significant (p = 0.020) and observed in 11 controls and 2 patients. Among the others that are not significant, a few examples of patient-specific and previously reported CNVs include deletions of 11q14.1 (DLG2), 22q11.21, and 14q21.1 (LRFN5). 16p13.3 deletion (RBFOX1), 3p14.2 duplication (CADPS), and 7p11.2 duplication (CCT6A) were some of the novel CNVs containing candidate genes. However, these observations need to be replicated in a larger sample size. In conclusion, this report constitutes an important foundation for future CNV studies in a relatively unexplored population. In addition, the data indicate that there are advantages in using an integrated approach for better identification of candidate CNVs for SZ and other mental health disorders.