Literature DB >> 21909109

Large-scale genome-wide association studies in East Asians identify new genetic loci influencing metabolic traits.

Young Jin Kim1, Min Jin Go, Cheng Hu, Chang Bum Hong, Yun Kyoung Kim, Ji Young Lee, Joo-Yeon Hwang, Ji Hee Oh, Dong-Joon Kim, Nam Hee Kim, Soeui Kim, Eun Jung Hong, Ji-Hyun Kim, Haesook Min, Yeonjung Kim, Rong Zhang, Weiping Jia, Yukinori Okada, Atsushi Takahashi, Michiaki Kubo, Toshihiro Tanaka, Naoyuki Kamatani, Koichi Matsuda, Taesung Park, Bermseok Oh, Kuchan Kimm, Daehee Kang, Chol Shin, Nam H Cho, Hyung-Lae Kim, Bok-Ghee Han, Jong-Young Lee, Yoon Shin Cho.   

Abstract

To identify the genetic bases for nine metabolic traits, we conducted a meta-analysis combining Korean genome-wide association results from the KARE project (n = 8,842) and the HEXA shared control study (n = 3,703). We verified the associations of the loci selected from the discovery meta-analysis in the replication stage (30,395 individuals from the BioBank Japan genome-wide association study and individuals comprising the Health2 and Shanghai Jiao Tong University Diabetes cohorts). We identified ten genome-wide significant signals newly associated with traits from an overall meta-analysis. The most compelling associations involved 12q24.11 (near MYL2) and 12q24.13 (in C12orf51) for high-density lipoprotein cholesterol, 2p21 (near SIX2-SIX3) for fasting plasma glucose, 19q13.33 (in RPS11) and 6q22.33 (in RSPO3) for renal traits, and 12q24.11 (near MYL2), 12q24.13 (in C12orf51 and near OAS1), 4q31.22 (in ZNF827) and 7q11.23 (near TBL2-BCL7B) for hepatic traits. These findings highlight previously unknown biological pathways for metabolic traits investigated in this study.

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Year:  2011        PMID: 21909109     DOI: 10.1038/ng.939

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  42 in total

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Journal:  Nat Genet       Date:  2008-01-13       Impact factor: 38.330

9.  A polygenic basis for four classical Fredrickson hyperlipoproteinemia phenotypes that are characterized by hypertriglyceridemia.

Authors:  Robert A Hegele; Matthew R Ban; Neil Hsueh; Brooke A Kennedy; Henian Cao; Guang Yong Zou; Sonia Anand; Salim Yusuf; Murray W Huff; Jian Wang
Journal:  Hum Mol Genet       Date:  2009-08-05       Impact factor: 6.150

10.  Newly identified loci that influence lipid concentrations and risk of coronary artery disease.

Authors:  Cristen J Willer; Serena Sanna; Anne U Jackson; Angelo Scuteri; Lori L Bonnycastle; Robert Clarke; Simon C Heath; Nicholas J Timpson; Samer S Najjar; Heather M Stringham; James Strait; William L Duren; Andrea Maschio; Fabio Busonero; Antonella Mulas; Giuseppe Albai; Amy J Swift; Mario A Morken; Narisu Narisu; Derrick Bennett; Sarah Parish; Haiqing Shen; Pilar Galan; Pierre Meneton; Serge Hercberg; Diana Zelenika; Wei-Min Chen; Yun Li; Laura J Scott; Paul A Scheet; Jouko Sundvall; Richard M Watanabe; Ramaiah Nagaraja; Shah Ebrahim; Debbie A Lawlor; Yoav Ben-Shlomo; George Davey-Smith; Alan R Shuldiner; Rory Collins; Richard N Bergman; Manuela Uda; Jaakko Tuomilehto; Antonio Cao; Francis S Collins; Edward Lakatta; G Mark Lathrop; Michael Boehnke; David Schlessinger; Karen L Mohlke; Gonçalo R Abecasis
Journal:  Nat Genet       Date:  2008-01-13       Impact factor: 38.330

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  153 in total

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Journal:  Am J Hum Genet       Date:  2013-08-22       Impact factor: 11.025

4.  Differential Lipid Response to Statins Is Associated With Variants in the BUD13-APOA5 Gene Region.

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Review 5.  Progress in Defining the Genetic Contribution to Type 2 Diabetes in Individuals of East Asian Ancestry.

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6.  A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci.

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Journal:  Genetics       Date:  2018-08-14       Impact factor: 4.562

7.  Genome-wide linkage and positional association analyses identify associations of novel AFF3 and NTM genes with triglycerides: the GenSalt study.

Authors:  Changwei Li; Lydia A L Bazzano; Dabeeru C Rao; James E Hixson; Jiang He; Dongfeng Gu; Charles C Gu; Lawrence C Shimmin; Cashell E Jaquish; Karen Schwander; De-Pei Liu; Jianfeng Huang; Fanghong Lu; Jie Cao; Shen Chong; Xiangfeng Lu; Tanika N Kelly
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8.  Genetic risk score combining six genetic variants associated with the cellular NRF2 expression levels correlates with Type 2 diabetes in the human population.

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9.  Discrete associations of the GCKR variant with metabolic risk in a Chinese population: longitudinal change analysis.

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10.  Disease risk factors identified through shared genetic architecture and electronic medical records.

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