当前位置: X-MOL 学术Nat. Commun. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Rare copy number variants in over 100,000 European ancestry subjects reveal multiple disease associations.
Nature Communications ( IF 16.6 ) Pub Date : 2020-01-14 , DOI: 10.1038/s41467-019-13624-1
Yun Rose Li 1, 2, 3 , Joseph T Glessner 1, 2 , Bradley P Coe 4 , Jin Li 1, 5 , Maede Mohebnasab 1 , Xiao Chang 1 , John Connolly 1 , Charlly Kao 1 , Zhi Wei 6 , Jonathan Bradfield 1 , Cecilia Kim 1 , Cuiping Hou 1 , Munir Khan 1 , Frank Mentch 1 , Haijun Qiu 1 , Marina Bakay 1 , Christopher Cardinale 1 , Maria Lemma 1 , Debra Abrams 1 , Andrew Bridglall-Jhingoor 1 , Meckenzie Behr 1 , Shanell Harrison 1 , George Otieno 1 , Alexandria Thomas 1 , Fengxiang Wang 1 , Rosetta Chiavacci 1 , Lawrence Wu 1 , Dexter Hadley 3 , Elizabeth Goldmuntz 2, 7 , Josephine Elia 2, 8, 9 , John Maris 2, 10 , Robert Grundmeier 11 , Marcella Devoto 2, 12, 13, 14 , Brendan Keating 1 , Michael March 1 , Renata Pellagrino 1 , Struan F A Grant 1, 2 , Patrick M A Sleiman 1 , Mingyao Li 14 , Evan E Eichler 4, 15 , Hakon Hakonarson 1, 2
Affiliation  

Copy number variants (CNVs) are suggested to have a widespread impact on the human genome and phenotypes. To understand the role of CNVs across human diseases, we examine the CNV genomic landscape of 100,028 unrelated individuals of European ancestry, using SNP and CGH array datasets. We observe an average CNV burden of ~650 kb, identifying a total of 11,314 deletion, 5625 duplication, and 2746 homozygous deletion CNV regions (CNVRs). In all, 13.7% are unreported, 58.6% overlap with at least one gene, and 32.8% interrupt coding exons. These CNVRs are significantly more likely to overlap OMIM genes (2.94-fold), GWAS loci (1.52-fold), and non-coding RNAs (1.44-fold), compared with random distribution (P < 1 × 10-3). We uncover CNV associations with four major disease categories, including autoimmune, cardio-metabolic, oncologic, and neurological/psychiatric diseases, and identify several drug-repurposing opportunities. Our results demonstrate robust frequency definition for large-scale rare variant association studies, identify CNVs associated with major disease categories, and illustrate the pleiotropic impact of CNVs in human disease.

中文翻译:

在100,000多个欧洲血统的受试者中,罕见的拷贝数变异显示出多种疾病关联。

拷贝数变异体(CNV)被认为对人类基因组和表型具有广泛的影响。为了了解CNV在人类疾病中的作用,我们使用SNP和CGH阵列数据集检查了100028例欧洲血统无关个体的CNV基因组格局。我们观察到〜650 kb的平均CNV负担,确定了总共11,314个缺失,5625个重复和2746个纯合缺失CNV区域(CNVR)。总计,未报告的基因占13.7%,与至少一个基因的重叠基因占58.6%,中断编码外显子占32.8%。与随机分布相比,这些CNVR与OMIM基因(2.94倍),GWAS基因座(1.52倍)和非编码RNA(1.44倍)重叠的可能性更高(P <1×10-3)。我们发现了CNV与四种主要疾病的关联,包括自身免疫,心脏代谢,肿瘤,以及神经系统/精神疾病,并确定一些替代药物的机会。我们的结果证明了用于大规模稀有变异关联研究的稳健频率定义,确定了与主要疾病类别相关的CNV,并说明了CNV对人类疾病的多效性影响。
更新日期:2020-01-14
down
wechat
bug