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Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia

Li, Zhiqiang, Chen, Jianhua, Yu, Hao, He, Lin, Xu, Yifeng, Zhang, Dai, Yi, Qizhong, Li, Changgui, Li, Xingwang, Shen, Jiawei, Song, Zhijian, Ji, Weidong, Wang, Meng, Zhou, Juan, Chen, Boyu, Liu, Yahui, Wang, Jiqiang, Wang, Peng, Yang, Ping, Wang, Qingzhong, Feng, Guoyin, Liu, Benxiu, Sun, Wensheng, Li, Baojie, He, Guang, Li, Weidong, Wan, Chunling, Xu, Qi, Li, Wenjin, Wen, Zujia, Liu, Ke, Huang, Fang, Ji, Jue, Ripke, Stephan, Yue, Weihua, Sullivan, Patrick F., O'Donovan, Michael C. and Shi, Yongyong 2017. Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia. Nature Genetics 49 , pp. 1576-1583. 10.1038/ng.3973

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Abstract

We conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and performed further transancestry meta-analyses with data from the Psychiatry Genomics Consortium (PGC2). Approximately 95% of the genome-wide significant (GWS) index alleles (or their proxies) from the PGC2 study were overrepresented in Chinese schizophrenia cases, including ∼50% that achieved nominal significance and ∼75% that continued to be GWS in the transancestry analysis. The Chinese-only analysis identified seven GWS loci; three of these also were GWS in the transancestry analyses, which identified 109 GWS loci, thus yielding a total of 113 GWS loci (30 novel) in at least one of these analyses. We observed improvements in the fine-mapping resolution at many susceptibility loci. Our results provide several lines of evidence supporting candidate genes at many loci and highlight some pathways for further research. Together, our findings provide novel insight into the genetic architecture and biological etiology of schizophrenia.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Subjects: R Medicine > R Medicine (General)
Publisher: Nature
ISSN: 1061-4036
Date of First Compliant Deposit: 23 November 2017
Date of Acceptance: 19 September 2017
Last Modified: 05 Jun 2020 15:45
URI: http://orca.cf.ac.uk/id/eprint/106955

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