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// Yoshiji Yamada 1, 2 , Jun Sakuma 2, 3, 4 , Ichiro Takeuchi 2, 4, 5 , Yoshiki Yasukochi 1, 2 , Kimihiko Kato 1, 6 , Mitsutoshi Oguri 1, 7 , Tetsuo Fujimaki 8 , Hideki Horibe 9 , Masaaki Muramatsu 10 , Motoji Sawabe 11 , Yoshinori Fujiwara 12 , Yu Taniguchi 12 , Shuichi Obuchi 13 , Hisashi Kawai 13 , Shoji Shinkai 14 , Seijiro Mori 15 , Tomio Arai 16 and Masashi Tanaka 17 1 Department of Human Functional Genomics, Advanced Science Research Promotion Center, Mie University, Tsu, Japan 2 CREST, Japan Science and Technology Agency, Kawaguchi, Japan 3 Computer Science Department, College of Information Science, University of Tsukuba, Tsukuba, Japan 4 RIKEN Center for Advanced Intelligence Project, Tokyo, Japan 5 Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan 6 Department of Internal Medicine, Meitoh Hospital, Nagoya, Japan 7 Department of Cardiology, Kasugai Municipal Hospital, Kasugai, Japan 8 Department of Cardiovascular Medicine, Inabe General Hospital, Inabe, Japan 9 Department of Cardiovascular Medicine, Gifu Prefectural Tajimi Hospital, Tajimi, Japan 10 Department of Molecular Epidemiology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan 11 Section of Molecular Pathology, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Tokyo, Japan 12 Research Team for Social Participation and Community Health, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan 13 Research Team for Promoting Support System for Home Care, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan 14 Research Team for Social Participation and Health Promotion, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan 15 Center for Promotion of Clinical Investigation, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan 16 Department of Pathology, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan 17 Department of Clinical Laboratory, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan Correspondence to: Yoshiji Yamada, email: yamada@gene.mie-u.ac.jp Keywords: body mass index, obesity, metabolic syndrome, genetics, exome-wide association study Received: February 15, 2017 Accepted: March 14, 2017 Published: April 07, 2017 ABSTRACT We have performed exome-wide association studies to identify genetic variants that influence body mass index or confer susceptibility to obesity or metabolic syndrome in Japanese. The exome-wide association study for body mass index included 12,890 subjects, and those for obesity and metabolic syndrome included 12,968 subjects (3954 individuals with obesity, 9014 controls) and 6817 subjects (3998 individuals with MetS, 2819 controls), respectively. Exome-wide association studies were performed with Illumina HumanExome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays. The relation of genotypes of single nucleotide polymorphisms to body mass index was examined by linear regression analysis, and that of allele frequencies of single nucleotide polymorphisms to obesity or metabolic syndrome was evaluated with Fisher’s exact test. The exome-wide association studies identified six, 11, and 40 single nucleotide polymorphisms as being significantly associated with body mass index, obesity ( P <1.21 × 10 –6 ), or metabolic syndrome ( P <1.20 × 10 –6 ), respectively. Subsequent multivariable logistic regression analysis with adjustment for age and sex revealed that three and five single nucleotide polymorphisms were related ( P < 0.05) to obesity or metabolic syndrome, respectively, with one of these latter polymorphisms—rs7350481 (C/T) at chromosome 11q23.3—also being significantly ( P < 3.13 × 10 –4 ) associated with metabolic syndrome. The polymorphism rs7350481 may thus be a novel susceptibility locus for metabolic syndrome in Japanese. In addition, single nucleotide polymorphisms in three genes ( CROT , TSC1 , RIN3 ) and at four loci ( ANKK1 , ZNF804B , CSRNP3 , 17p11.2) were implicated as candidate determinants of obesity and metabolic syndrome, respectively.
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