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

Young Jin Kim, 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 KuboToshihiro 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

Research output: Contribution to journalArticlepeer-review

230 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)990-997
Number of pages8
JournalNature Genetics
Volume43
Issue number10
DOIs
Publication statusPublished - 2011 Oct

Bibliographical note

Funding Information:
This work was supported by grants from Korea Centers for Disease Control and Prevention (4845-301, 4851-302, 4851-307) and an intramural grant from the Korea National Institute of Health (2010-N73002-00), the Republic of Korea. The Shanghai study was supported by grants from National 973 Program (2011CB504001), National Natural Science Foundation of China (30800617), China. BioBank Japan project is supported by the Ministry of Education, Culture, Sports, Science and Technology of Japan.

ASJC Scopus subject areas

  • Genetics

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