👤 Chun Wang

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Also published as: A Wang, Ai-Ling Wang, Ai-Ting Wang, Aihua Wang, Aijun Wang, Aili Wang, Aimin Wang, Aiting Wang, Aixian Wang, Aiyun Wang, Aizhong Wang, Alexander Wang, Alice Wang, Allen Wang, Anlai Wang, Anli Wang, Annette Wang, Anni Wang, Anqi Wang, Anthony Z Wang, Anxiang Wang, Anxin Wang, Ao Wang, Aoli Wang, B R Wang, B Wang, Baihan Wang, Baisong Wang, Baitao Wang, Bangchen Wang, Banghui Wang, Bangmao Wang, Bangshing Wang, Bao Wang, Bao-Long Wang, Baocheng Wang, Baofeng Wang, Baogui Wang, Baojun Wang, Baoli Wang, Baolong Wang, Baoming Wang, Baosen Wang, Baowei Wang, Baoying Wang, Baoyun Wang, Bei Bei Wang, Bei Wang, Beibei Wang, Beilan Wang, Beilei Wang, Ben Wang, Benjamin H Wang, Benzhong Wang, Bi Wang, Bi-Dar Wang, Biao Wang, Bicheng Wang, Bijue Wang, Bin Wang, Bin-Xue Wang, Binbin Wang, Bing Qing Wang, Bing Wang, Binghai Wang, Binghan Wang, Bingjie Wang, Binglong Wang, Bingnan Wang, Bingyan Wang, Bingyu Wang, Binquan Wang, Biqi Wang, Bo Wang, Bochu Wang, Boyu Wang, Bruce Wang, C Wang, C Z Wang, Cai Ren Wang, Cai-Hong Wang, Cai-Yun Wang, Cailian Wang, Caiqin Wang, Caixia Wang, Caiyan Wang, Can Wang, Cangyu Wang, Carol A Wang, Catherine Ruiyi Wang, Cenxuan Wang, Chan Wang, Chang Wang, Chang-Yun Wang, Changduo Wang, Changjing Wang, Changliang Wang, Changlong Wang, Changqian Wang, Changtu Wang, Changwei Wang, Changying Wang, Changyu Wang, Changyuan Wang, Changzhen Wang, Chao Wang, Chao-Jun Wang, Chao-Yung Wang, Chaodong Wang, Chaofan Wang, Chaohan Wang, Chaohui Wang, Chaojie Wang, Chaokui Wang, Chaomeng Wang, Chaoqun Wang, Chaoxian Wang, Chaoyi Wang, Chaoyu Wang, Chaozhan Wang, Charles C N Wang, Chau-Jong Wang, Chen Wang, Chen-Cen Wang, Chen-Ma Wang, Chen-Yu Wang, Chenchen Wang, Chenfei Wang, Cheng An Wang, Cheng Wang, Cheng-Cheng Wang, Cheng-Jie Wang, Cheng-zhang Wang, Chengbin Wang, Chengcheng Wang, Chenggang Wang, Chenghao Wang, Chenghua Wang, Chengjian Wang, Chengjun Wang, Chenglin Wang, Chenglong Wang, Chengniu Wang, Chengqiang Wang, Chengshuo Wang, Chenguang Wang, Chengwen Wang, Chengyan Wang, Chengyu Wang, Chengze Wang, Chenji Wang, Chenliang Wang, Chenwei Wang, Chenxi Wang, Chenxin Wang, Chenxuan Wang, Chenyang Wang, Chenyao Wang, Chenyin Wang, Chenyu Wang, Chenzi Wang, Chi Chiu Wang, Chi Wang, Chi-Ping Wang, Chia-Chuan Wang, Chia-Lin Wang, Chien-Hsun Wang, Chien-Wei Wang, Chih-Chun Wang, Chih-Hao Wang, Chih-Hsien Wang, Chih-Liang Wang, Chih-Yang Wang, Chih-Yuan Wang, Chijia Wang, Ching C Wang, Ching-Jen Wang, Chiou-Miin Wang, Chong Wang, Chongjian Wang, Chonglong Wang, Chongmin Wang, Chongze Wang, Christina Wang, Christine Wang, Chu Wang, Chuan Wang, Chuan-Chao Wang, Chuan-Hui Wang, Chuan-Jiang Wang, Chuan-Wen Wang, Chuang Wang, Chuanhai Wang, Chuansen Wang, Chuansheng Wang, Chuanxin Wang, Chuanyue Wang, Chuduan Wang, Chun-Chieh Wang, Chun-Juan Wang, Chun-Li Wang, Chun-Lin Wang, Chun-Ting Wang, Chun-Xia Wang, Chung-Hsi Wang, Chung-Hsing Wang, Chung-Teng Wang, Chunguo Wang, Chunhong Wang, Chuning Wang, Chunjiong Wang, Chunjuan Wang, Chunle Wang, Chunli Wang, Chunlong Wang, Chunmei Wang, Chunsheng Wang, Chunting Wang, Chunxia Wang, Chunxue Wang, Chunyan Wang, Chunyang Wang, Chunyi Wang, Chunyu Wang, Chuyao Wang, Cindy Wang, Ciyang Wang, Cong Wang, Congcong Wang, Congrong Wang, Congrui Wang, Cui Wang, Cui-Fang Wang, Cui-Shan Wang, Cuili Wang, Cuiling Wang, Cuizhe Wang, Cun-Yu Wang, Cunchuan Wang, Cunyi Wang, D Wang, Da Wang, Da-Cheng Wang, Da-Li Wang, Da-Yan Wang, Da-Zhi Wang, Dadong Wang, Dai Wang, Daijun Wang, Daiwei Wang, Daixi Wang, Dajia Wang, Dake Wang, Dali Wang, Dalong Wang, Dalu Wang, Dan Wang, Dan-Dan Wang, Danan Wang, Dandan Wang, Danfeng Wang, Dang Wang, Dangfeng Wang, Danling Wang, Danqing Wang, Danxin Wang, Danyang Wang, Dao Wen Wang, Dao-Wen Wang, Dao-Xin Wang, Daolong Wang, Daoping Wang, Daozhong Wang, Dapeng Wang, Daping Wang, Daqi Wang, Daqing Wang, David Q H Wang, David Q-H Wang, David Wang, Dawei Wang, Dayan Wang, Dayong Wang, Dazhi Wang, De-He Wang, Dedong Wang, Dehao Wang, Deli Wang, Delin Wang, Delong Wang, Demin Wang, Deming Wang, Dengbin Wang, Dennis Qing Wang, Dennis Wang, Deqi Wang, Deshou Wang, Dezhong Wang, Di Wang, Dinghui Wang, Dingting Wang, Dingxiang Wang, Dong D Wang, Dong Hao Wang, Dong Wang, Dong-Dong Wang, Dong-Jie Wang, Dong-Mei Wang, DongWei Wang, Dongdong Wang, Donggen Wang, Donghao Wang, Donghong Wang, Donghui Wang, Dongliang Wang, Donglin Wang, Dongmei Wang, Dongqin Wang, Dongshi Wang, Dongxia Wang, Dongxu Wang, Dongyan Wang, Dongyang Wang, Dongyi Wang, Dongying Wang, Dongyu Wang, Doudou Wang, Du Wang, Duan Wang, Duanyang Wang, Duo-Ping Wang, E Wang, Edward Wang, En-bo Wang, En-hua Wang, Endi Wang, Enhua Wang, Er-Jin Wang, Erfei Wang, Erika Y Wang, Ermao Wang, Erming Wang, Ertao Wang, Eryao Wang, Eunice S Wang, Exing Wang, F Wang, Fa-Kai Wang, Fan Wang, Fanchang Wang, Fang Wang, Fang-Tao Wang, Fangfang Wang, Fangjie Wang, Fangjun Wang, Fangyan Wang, Fangyong Wang, Fangyu Wang, Fanhua Wang, Fanwen Wang, Fanxiong Wang, Fei Wang, Fei-Fei Wang, Fei-Yan Wang, Feida Wang, Feifei Wang, Feijie Wang, Feimiao Wang, Feixiang Wang, Feiyan Wang, Fen Wang, Feng Wang, Feng-Sheng Wang, Fengchong Wang, Fengge Wang, Fenghua Wang, Fengliang Wang, Fenglin Wang, Fengling Wang, Fengqiang Wang, Fengyang Wang, Fengying Wang, Fengyong Wang, Fengyun Wang, Fengzhen Wang, Fengzhong Wang, Fu Wang, Fu-Sheng Wang, Fu-Yan Wang, Fu-Zhen Wang, Fubao Wang, Fubing Wang, Fudi Wang, Fuhua Wang, Fuqiang Wang, Furong Wang, Fuwen Wang, Fuxin Wang, Fuyan Wang, G Q Wang, G Wang, G-W Wang, Gan Wang, Gang Wang, Ganggang Wang, Ganglin Wang, Gangyang Wang, Ganyu Wang, Gao T Wang, Gao Wang, Gaofu Wang, Gaopin Wang, Gavin Wang, Ge Wang, Geng Wang, Genghao Wang, Gengsheng Wang, Gongming Wang, Guan Wang, Guan-song Wang, Guandi Wang, Guanduo Wang, Guang Wang, Guang-Jie Wang, Guang-Rui Wang, Guangdi Wang, Guanghua Wang, Guanghui Wang, Guangliang Wang, Guangming Wang, Guangsuo Wang, Guangwen Wang, Guangyan Wang, Guangzhi Wang, Guanrou Wang, Guanru Wang, Guansong Wang, Guanyun Wang, Gui-Qi Wang, Guibin Wang, Guihu Wang, Guihua Wang, Guimin Wang, Guiping Wang, Guiqun Wang, Guixin Wang, Guixue Wang, Guiying Wang, Guo-Du Wang, Guo-Hua Wang, Guo-Liang Wang, Guo-Ping Wang, Guo-Quan Wang, Guo-hong Wang, GuoYou Wang, Guobin Wang, Guobing Wang, Guodong Wang, Guohang Wang, Guohao Wang, Guoliang Wang, Guoling Wang, Guoping Wang, Guoqian Wang, Guoqiang Wang, Guoqing Wang, Guorong Wang, Guowen Wang, Guoxiang Wang, Guoxiu Wang, Guoyi Wang, Guoying Wang, Guozheng Wang, H J Wang, H Wang, H X Wang, H Y Wang, H-Y Wang, Hai Bo Wang, Hai Wang, Hai Yang Wang, Hai-Feng Wang, Hai-Jun Wang, Hai-Long Wang, Haibin Wang, Haibing Wang, Haibo Wang, Haichao Wang, Haichuan Wang, Haifei Wang, Haifeng Wang, Haihe Wang, Haihong Wang, Haihua Wang, Haijiao Wang, Haijing Wang, Haijiu Wang, Haikun Wang, Hailei Wang, Hailin Wang, Hailing Wang, Hailong Wang, Haimeng Wang, Haina Wang, Haining Wang, Haiping Wang, Hairong Wang, Haitao Wang, Haiwei Wang, Haixia Wang, Haixin Wang, Haixing Wang, Haiyan Wang, Haiying Wang, Haiyong Wang, Haiyun Wang, Haizhen Wang, Han Wang, Hanbin Wang, Hanbing Wang, Hanchao Wang, Handong Wang, Hang Wang, Hangzhou Wang, Hanmin Wang, Hanping Wang, Hanqi Wang, Hanying Wang, Hanyu Wang, Hanzhi Wang, Hao Wang, Hao-Ching Wang, Hao-Hua Wang, Hao-Tian Wang, Hao-Yu Wang, Haobin Wang, Haochen Wang, Haohao Wang, Haohui Wang, Haojie Wang, Haolong Wang, Haomin Wang, Haoming Wang, Haonan Wang, Haoping Wang, Haoqi Wang, Haoran Wang, Haowei Wang, Haoxin Wang, Haoyang Wang, Haoyu Wang, Haozhou Wang, He Wang, He-Cheng Wang, He-Ling Wang, He-Ping Wang, He-Tong Wang, Hebo Wang, Hechuan Wang, Heling Wang, Hemei Wang, Heming Wang, Heng Wang, Heng-Cai Wang, Hengjiao Wang, Hengjun Wang, Hequn Wang, Hesuiyuan Wang, Heyong Wang, Hezhi Wang, Hong Wang, Hong Yi Wang, Hong-Gang Wang, Hong-Hui Wang, Hong-Kai Wang, Hong-Qin Wang, Hong-Wei Wang, Hong-Xia Wang, Hong-Yan Wang, Hong-Yang Wang, Hong-Ying Wang, Hongbin Wang, Hongbing Wang, Hongbo Wang, Hongcai Wang, Hongda Wang, Hongdan Wang, Hongfang Wang, Hongjia Wang, Hongjian Wang, Hongjie Wang, Hongjuan Wang, Hongkun Wang, Honglei Wang, Hongli Wang, Honglian Wang, Honglun Wang, Hongmei Wang, Hongpin Wang, Hongqian Wang, Hongshan Wang, Hongsheng Wang, Hongtao Wang, Hongwei Wang, Hongxia Wang, Hongxin Wang, Hongyan Wang, Hongyang Wang, Hongyi Wang, Hongyin Wang, Hongying Wang, Hongyu Wang, Hongyuan Wang, Hongyue Wang, Hongyun Wang, Hongze Wang, Hongzhan Wang, Hongzhuang Wang, Horng-Dar Wang, Houchun Wang, Hsei-Wei Wang, Hsueh-Chun Wang, Hu WANG, Hua Wang, Hua-Qin Wang, Hua-Wei Wang, Huabo Wang, Huafei Wang, Huai-Zhou Wang, Huaibing Wang, Huaili Wang, Huaizhi Wang, Huajin Wang, Huajing Wang, Hualin Wang, Hualing Wang, Huan Wang, Huan-You Wang, Huang Wang, Huanhuan Wang, Huanyu Wang, Huaquan Wang, Huating Wang, Huawei Wang, Huaxiang Wang, Huayang Wang, Huei Wang, Hui Miao Wang, Hui Wang, Hui-Hui Wang, Hui-Li Wang, Hui-Nan Wang, Hui-Yu Wang, HuiYue Wang, Huie Wang, Huiguo Wang, Huihua Wang, Huihui Wang, Huijie Wang, Huijun Wang, Huilun Wang, Huimei Wang, Huimin Wang, Huina Wang, Huiping Wang, Huiquan Wang, Huiqun Wang, Huishan Wang, Huiting Wang, Huiwen Wang, Huixia Wang, Huiyan Wang, Huiyang Wang, Huiyao Wang, Huiying Wang, Huiyu Wang, Huizhen Wang, Huizhi Wang, Huming Wang, I-Ching Wang, Iris X Wang, Isabel Z Wang, J J Wang, J P Wang, J Q Wang, J Wang, J Z Wang, J-Y Wang, Jacob E Wang, James Wang, Jeffrey Wang, Jen-Chun Wang, Jen-Chywan Wang, Jennifer E Wang, Jennifer T Wang, Jennifer X Wang, Jenny Y Wang, Jeremy R Wang, Jeremy Wang, Ji M Wang, Ji Wang, Ji-Nuo Wang, Ji-Yang Wang, Ji-Yao Wang, Ji-zheng Wang, Jia Bei Wang, Jia Bin Wang, Jia Wang, Jia-Liang Wang, Jia-Lin Wang, Jia-Mei Wang, Jia-Peng Wang, Jia-Qi Wang, Jia-Qiang Wang, Jia-Ying Wang, Jia-Yu Wang, Jiabei Wang, Jiabo Wang, Jiafeng Wang, Jiafu Wang, Jiahao Wang, Jiahui Wang, Jiajia Wang, Jiakun Wang, Jiale Wang, Jiali Wang, Jialiang Wang, Jialin Wang, Jialing Wang, Jiamin Wang, Jiaming Wang, Jian Wang, Jian'an Wang, Jian-Bin Wang, Jian-Guo Wang, Jian-Hong Wang, Jian-Long Wang, Jian-Wei Wang, Jian-Xiong Wang, Jian-Yong Wang, Jian-Zhi Wang, Jian-chun Wang, Jianan Wang, Jianbing Wang, Jianbo Wang, Jianding Wang, Jianfang Wang, Jianfei Wang, Jiang Wang, Jiangbin Wang, Jiangbo Wang, Jianghua Wang, Jianghui Wang, Jiangong Wang, Jianguo Wang, Jianhao Wang, Jianhua Wang, Jianhui Wang, Jiani Wang, Jianjiao Wang, Jianjie Wang, Jianjun Wang, Jianle Wang, Jianli Wang, Jianlin Wang, Jianliu Wang, Jianlong Wang, Jianmei Wang, Jianmin Wang, Jianning Wang, Jianping Wang, Jianqin Wang, Jianqing Wang, Jianqun Wang, Jianru Wang, Jianshe Wang, Jianshu Wang, Jiantao Wang, Jianwei Wang, Jianwu Wang, Jianxiang Wang, Jianxin Wang, Jianye Wang, Jianying Wang, Jianyong Wang, Jianyu Wang, Jianzhang Wang, Jianzhi Wang, Jiao Wang, Jiaojiao Wang, Jiapan Wang, Jiaping Wang, Jiaqi Wang, Jiaqian Wang, Jiatao Wang, Jiawei Wang, Jiawen Wang, Jiaxi Wang, Jiaxin Wang, Jiaxing Wang, Jiaxuan Wang, Jiayan Wang, Jiayang Wang, Jiayi Wang, Jiaying Wang, Jiayu Wang, Jiazheng Wang, Jiazhi Wang, Jie Jin Wang, Jie Wang, Jieda Wang, Jieh-Neng Wang, Jiemei Wang, Jieqi Wang, Jieyan Wang, Jieyu Wang, Jifei Wang, Jiheng Wang, Jihong Wang, Jiliang Wang, Jilin Wang, Jin Wang, Jin'e Wang, Jin-Bao Wang, Jin-Cheng Wang, Jin-Da Wang, Jin-E Wang, Jin-Juan Wang, Jin-Liang Wang, Jin-Xia Wang, Jin-Xing Wang, Jincheng Wang, Jindan Wang, Jinfei Wang, Jinfeng Wang, Jinfu Wang, Jing J Wang, Jing Wang, Jing-Hao Wang, Jing-Huan Wang, Jing-Jing Wang, Jing-Long Wang, Jing-Min Wang, Jing-Shi Wang, Jing-Wen Wang, Jing-Xian Wang, Jing-Yi Wang, Jing-Zhai Wang, Jingang Wang, Jingchun Wang, Jingfan Wang, Jingfeng Wang, Jingheng Wang, Jinghong Wang, Jinghua Wang, Jinghuan Wang, Jingjing Wang, Jingkang Wang, Jinglin Wang, Jingmin Wang, Jingnan Wang, Jingqi Wang, Jingru Wang, Jingtong Wang, Jingwei Wang, Jingwen Wang, Jingxiao Wang, Jingyang Wang, Jingyi Wang, Jingying Wang, Jingyu Wang, Jingyue Wang, Jingyun Wang, Jingzhou Wang, Jinhai Wang, Jinhao Wang, Jinhe Wang, Jinhua Wang, Jinhuan Wang, Jinhui Wang, Jinjie Wang, Jinjin Wang, Jinkang Wang, Jinling Wang, Jinlong Wang, Jinmeng Wang, Jinning Wang, Jinping Wang, Jinqiu Wang, Jinrong Wang, Jinru Wang, Jinsong Wang, Jintao Wang, Jinxia Wang, Jinxiang Wang, Jinyang Wang, Jinyu Wang, Jinyue Wang, Jinyun Wang, Jinzhu Wang, Jiou Wang, Jipeng Wang, Jiqing Wang, Jiqiu Wang, Jisheng Wang, Jiu Wang, Jiucun Wang, Jiun-Ling Wang, Jiwen Wang, Jixuan Wang, Jiyan Wang, Jiying Wang, Jiyong Wang, Jizheng Wang, John Wang, Jou-Kou Wang, Joy Wang, Ju Wang, Juan Wang, Jue Wang, Jueqiong Wang, Jufeng Wang, Julie Wang, Juling Wang, Jun Kit Wang, Jun Wang, Jun Yi Wang, Jun-Feng Wang, Jun-Jie Wang, Jun-Jun Wang, Jun-Ling Wang, Jun-Sheng Wang, Jun-Sing Wang, Jun-Zhuo Wang, Jundong Wang, Junfeng Wang, Jung-Pan Wang, Junhong Wang, Junhua Wang, Junhui Wang, Junjiang Wang, Junjie Wang, Junjun Wang, Junkai Wang, Junke Wang, Junli Wang, Junlin Wang, Junling Wang, Junmei Wang, Junmin Wang, Junpeng Wang, Junping Wang, Junqin Wang, Junqing Wang, Junrui Wang, Junsheng Wang, Junshi Wang, Junshuang Wang, Junwen Wang, Junxiao Wang, Junya Wang, Junying Wang, Junyu Wang, Justin Wang, Jutao Wang, Juxiang Wang, K Wang, Kai Wang, Kai-Kun Wang, Kai-Wen Wang, Kaicen Wang, Kaihao Wang, Kaihe Wang, Kaihong Wang, Kaijie Wang, Kaijuan Wang, Kailu Wang, Kaiming Wang, Kaining Wang, Kaiting Wang, Kaixi Wang, Kaixu Wang, Kaiyan Wang, Kaiyuan Wang, Kaiyue Wang, Kan Wang, Kangli Wang, Kangling Wang, Kangmei Wang, Kangning Wang, Ke Wang, Ke-Feng Wang, KeShan Wang, Kehan Wang, Kehao Wang, Kejia Wang, Kejian Wang, Kejun Wang, Keke Wang, Keming Wang, Kenan Wang, Keqing Wang, Kesheng Wang, Kexin Wang, Keyan Wang, Keyi Wang, Keyun Wang, Kongyan Wang, Kuan Hong Wang, Kui Wang, Kun Wang, Kunhua Wang, Kunpeng Wang, Kunzheng Wang, L F Wang, L M Wang, L Wang, L Z Wang, L-S Wang, Laidi Wang, Laijian Wang, Laiyuan Wang, Lan Wang, Lan-Wan Wang, Lan-lan Wang, Lanlan Wang, Larry Wang, Le Wang, Le-Xin Wang, Ledan Wang, Lee-Kai Wang, Lei P Wang, Lei Wang, Lei-Lei Wang, Leiming Wang, Leishen Wang, Leli Wang, Leran Wang, Lexin Wang, Leying Wang, Li Chun Wang, Li Dong Wang, Li Wang, Li-Dong Wang, Li-E Wang, Li-Juan Wang, Li-Li Wang, Li-Na Wang, Li-San Wang, Li-Ting Wang, Li-Xin Wang, Li-Yong Wang, LiLi Wang, Lian Wang, Lianchun Wang, Liang Wang, Liang-Yan Wang, Liangfu Wang, Lianghai Wang, Liangli Wang, Liangliang Wang, Liangxu Wang, Lianshui Wang, Lianyong Wang, Libo Wang, Lichan Wang, Lichao Wang, Liewei Wang, Lifang Wang, Lifei Wang, Lifen Wang, Lifeng Wang, Ligang Wang, Lihong Wang, Lihua Wang, Lihui Wang, Lijia Wang, Lijin Wang, Lijing Wang, Lijuan Wang, Lijun Wang, Liling Wang, Lily Wang, Limeng Wang, Limin Wang, Liming Wang, Lin Wang, Lin-Fa Wang, Lin-Yu Wang, Lina Wang, Linfang Wang, Ling Jie Wang, Ling Wang, Ling-Ling Wang, Lingbing Wang, Lingda Wang, Linghua Wang, Linghuan Wang, Lingli Wang, Lingling Wang, Lingyan Wang, Lingzhi Wang, Linhua Wang, Linhui Wang, Linjie Wang, Linli Wang, Linlin Wang, Linping Wang, Linshu Wang, Linshuang Wang, Lintao Wang, Linxuan Wang, Linying Wang, Linyuan Wang, Liping Wang, Liqing Wang, Liqun Wang, Lirong Wang, Litao Wang, Liting Wang, Liu Wang, Liusong Wang, Liuyang Wang, Liwei Wang, Lixia Wang, Lixian Wang, Lixiang Wang, Lixin Wang, Lixing Wang, Lixiu Wang, Liyan Wang, Liyi Wang, Liying Wang, Liyong Wang, Liyuan Wang, Liyun Wang, Long Wang, Longcai Wang, Longfei Wang, Longsheng Wang, Longxiang Wang, Lou-Pin Wang, Lu Wang, Lu-Lu Wang, Lueli Wang, Lufang Wang, Luhong Wang, Luhui Wang, Lujuan Wang, Lulu Wang, Luofu Wang, Luping Wang, Luting Wang, Luwen Wang, Luxiang Wang, Luya Wang, Luyao Wang, Luyun Wang, Lynn Yuning Wang, M H Wang, M Wang, M Y Wang, M-J Wang, Maiqiu Wang, Man Wang, Mangju Wang, Manli Wang, Mao-Xin Wang, Maochun Wang, Maojie Wang, Maoju Wang, Mark Wang, Mei Wang, Mei-Gui Wang, Mei-Xia Wang, Meiding Wang, Meihui Wang, Meijun Wang, Meiling Wang, Meixia Wang, Melissa T Wang, Meng C Wang, Meng Wang, Meng Yu Wang, Meng-Dan Wang, Meng-Lan Wang, Meng-Meng Wang, Meng-Ru Wang, Meng-Wei Wang, Meng-Ying Wang, Meng-hong Wang, Mengge Wang, Menghan Wang, Menghui Wang, Mengjiao Wang, Mengjing Wang, Mengjun Wang, Menglong Wang, Menglu Wang, Mengmeng Wang, Mengqi Wang, Mengru Wang, Mengshi Wang, Mengwen Wang, Mengxiao Wang, Mengya Wang, Mengyao Wang, Mengying Wang, Mengyuan Wang, Mengyue Wang, Mengyun Wang, Mengze Wang, Mengzhao Wang, Mengzhi Wang, Mian Wang, Miao Wang, Mimi Wang, Min Wang, Min-sheng Wang, Ming Wang, Ming-Chih Wang, Ming-Hsi Wang, Ming-Jie Wang, Ming-Wei Wang, Ming-Yang Wang, Ming-Yuan Wang, Mingchao Wang, Mingda Wang, Minghua Wang, Minghuan Wang, Minghui Wang, Mingji Wang, Mingjin Wang, Minglei Wang, Mingliang Wang, Mingmei Wang, Mingming Wang, Mingqiang Wang, Mingrui Wang, Mingsong Wang, Mingxi Wang, Mingxia Wang, Mingxun Wang, Mingya Wang, Mingyang Wang, Mingyi Wang, Mingyu Wang, Mingzhi Wang, Mingzhu Wang, Minjie Wang, Minjun Wang, Minmin Wang, Minxian Wang, Minxiu Wang, Minzhou Wang, Miranda C Wang, Mo Wang, Mofei Wang, Monica Wang, Mu Wang, Mutian Wang, Muxiao Wang, Muxuan Wang, N Wang, Na Wang, Nan Wang, Nana Wang, Nanbu Wang, Nannan Wang, Nanping Wang, Neng Wang, Ni Wang, Niansong Wang, Ning Wang, Ningjian Wang, Ningli Wang, Ningyuan Wang, Nuan Wang, Oliver Wang, Ouchen Wang, P Jeremy Wang, P L Wang, P N Wang, P Wang, Pai Wang, Pan Wang, Pan-Pan Wang, Panfeng Wang, Panliang Wang, Pei Chang Wang, Pei Wang, Pei-Hua Wang, Pei-Jian Wang, Pei-Juan Wang, Pei-Wen Wang, Pei-Yu Wang, Peichang Wang, Peigeng Wang, Peihe Wang, Peijia Wang, Peijuan Wang, Peijun Wang, Peilin Wang, Peipei Wang, Peirong Wang, Peiwen Wang, Peixi Wang, Peiyao Wang, Peiyin Wang, Peng Wang, Peng-Cheng Wang, Pengbo Wang, Pengchao Wang, Pengfei Wang, Pengjie Wang, Pengju Wang, Penglai Wang, Penglong Wang, Pengpu Wang, Pengtao Wang, Pengxiang Wang, Pengyu Wang, Pin Wang, Ping Wang, Pingchuan Wang, Pingfeng Wang, Pingping Wang, Pintian Wang, Po-Jen Wang, Pu Wang, Q Wang, Q Z Wang, Qi Wang, Qi-Bing Wang, Qi-En Wang, Qi-Jia Wang, Qi-Qi Wang, Qian Wang, Qian-Liang Wang, Qian-Wen Wang, Qian-Zhu Wang, Qian-fei Wang, Qianbao Wang, Qiang Wang, Qiang-Sheng Wang, Qiangcheng Wang, Qianghu Wang, Qiangqiang Wang, Qianjin Wang, Qianliang Wang, Qianqian Wang, Qianrong Wang, Qianru Wang, Qianwen Wang, Qianxu Wang, Qiao Wang, Qiao-Ping Wang, Qiaohong Wang, Qiaoqi Wang, Qiaoqiao Wang, Qifan Wang, Qifei Wang, Qifeng Wang, Qigui Wang, Qihao Wang, Qihua Wang, Qijia Wang, Qiming Wang, Qin Wang, Qing Jun Wang, Qing K Wang, Qing Kenneth Wang, Qing Mei Wang, Qing Wang, Qing-Bin Wang, Qing-Dong Wang, Qing-Jin Wang, Qing-Liang Wang, Qing-Mei Wang, Qing-Yan Wang, Qing-Yuan Wang, Qing-Yun Wang, QingDong Wang, Qingchun Wang, Qingfa Wang, Qingfeng Wang, Qinghang Wang, Qingliang Wang, Qinglin Wang, Qinglu Wang, Qingming Wang, Qingping Wang, Qingqing Wang, Qingshi Wang, Qingshui Wang, Qingsong Wang, Qingtong Wang, Qingyong Wang, Qingyu Wang, Qingyuan Wang, Qingyun Wang, Qingzhong Wang, Qinqin Wang, Qinrong Wang, Qintao Wang, Qinwen Wang, Qinyun Wang, Qiong Wang, Qiqi Wang, Qirui Wang, Qishan Wang, Qiu-Ling Wang, Qiu-Xia Wang, Qiuhong Wang, Qiuli Wang, Qiuling Wang, Qiuning Wang, Qiuping Wang, Qiushi Wang, Qiuting Wang, Qiuyan Wang, Qiuyu Wang, Qiwei Wang, Qixue Wang, Qiyu Wang, Qiyuan Wang, Quan Wang, Quan-Ming Wang, Quanli Wang, Quanren Wang, Quanxi Wang, Qun Wang, Qunxian Wang, Qunzhi Wang, R Wang, Ran Wang, Ranjing Wang, Ranran Wang, Re-Hua Wang, Ren Wang, Rencheng Wang, Renjun Wang, Renqian Wang, Renwei Wang, Renxi Wang, Renxiao Wang, Renyuan Wang, Rihua Wang, Rikang Wang, Rixiang Wang, Robert Yl Wang, Rong Wang, Rong-Chun Wang, Rong-Rong Wang, Rong-Tsorng Wang, RongRong Wang, Rongjia Wang, Rongping Wang, Rongyun Wang, Ru Wang, RuNan Wang, Ruey-Yun Wang, Rufang Wang, Ruhan Wang, Rui Wang, Rui-Hong Wang, Rui-Min Wang, Rui-Ping Wang, Rui-Rui Wang, Ruibin Wang, Ruibing Wang, Ruibo Wang, Ruicheng Wang, Ruifang Wang, Ruijing Wang, Ruimeng Wang, Ruimin Wang, Ruiming Wang, Ruinan Wang, Ruining Wang, Ruiquan Wang, Ruiwen Wang, Ruixian Wang, Ruixin Wang, Ruixuan Wang, Ruixue Wang, Ruiying Wang, Ruizhe Wang, Ruizhi Wang, Rujie Wang, Ruling Wang, Ruming Wang, Runci Wang, Runuo Wang, Runze Wang, Runzhi Wang, Ruo-Nan Wang, Ruo-Ran Wang, Ruonan Wang, Ruosu Wang, Ruoxi Wang, Rurong Wang, Ruting Wang, Ruxin Wang, Ruxuan Wang, Ruyue Wang, S L Wang, S S Wang, S Wang, S X Wang, Sa A Wang, Sa Wang, Saifei Wang, Saili Wang, Sainan Wang, Saisai Wang, Sangui Wang, Sanwang Wang, Sasa Wang, Sen Wang, Seok Mui Wang, Seungwon Wang, Sha Wang, Shan Wang, Shan-Shan Wang, Shang Wang, Shangyu Wang, Shanshan Wang, Shao-Kang Wang, Shaochun Wang, Shaohsu Wang, Shaokun Wang, Shaoli Wang, Shaolian Wang, Shaoshen Wang, Shaowei Wang, Shaoyi Wang, Shaoying Wang, Shaoyu Wang, Shaozheng Wang, Shasha Wang, Shau-Chun Wang, Shawn Wang, Shen Wang, Shen-Nien Wang, Shenao Wang, Sheng Wang, Sheng-Min Wang, Sheng-Nan Wang, Sheng-Ping Wang, Sheng-Quan Wang, Sheng-Yang Wang, Shengdong Wang, Shengjie Wang, Shengli Wang, Shengqi Wang, Shengya Wang, Shengyao Wang, Shengyu Wang, Shengyuan Wang, Shenqi Wang, Sheri Wang, Shi Wang, Shi-Cheng Wang, Shi-Han Wang, Shi-Qi Wang, Shi-Xin Wang, Shi-Yao Wang, Shibin Wang, Shichao Wang, Shicung Wang, Shidong Wang, Shifa Wang, Shifeng Wang, Shih-Wei Wang, Shihan Wang, Shihao Wang, Shihua Wang, Shijie Wang, Shijin Wang, Shijun Wang, Shikang Wang, Shimiao Wang, Shiqi Wang, Shiqiang Wang, Shitao Wang, Shitian Wang, Shiwen Wang, Shixin Wang, Shixuan Wang, Shiyang Wang, Shiyao Wang, Shiyin Wang, Shiyu Wang, Shiyuan Wang, Shiyue Wang, Shizhi Wang, Shouli Wang, Shouling Wang, Shouzhi Wang, Shu Wang, Shu-Huei Wang, Shu-Jin Wang, Shu-Ling Wang, Shu-Na Wang, Shu-Song Wang, Shu-Xia Wang, Shu-qiang Wang, Shuai Wang, Shuaiqin Wang, Shuang Wang, Shuang-Shuang Wang, Shuang-Xi Wang, Shuangyuan Wang, Shubao Wang, Shudan Wang, Shuge Wang, Shuguang Wang, Shuhe Wang, Shuiliang Wang, Shuiyun Wang, Shujin Wang, Shukang Wang, Shukui Wang, Shun Wang, Shuning Wang, Shunjun Wang, Shunran Wang, Shuo Wang, Shuping Wang, Shuqi Wang, Shuqing Wang, Shuren Wang, Shusen Wang, Shusheng Wang, Shushu Wang, Shuu-Jiun Wang, Shuwei Wang, Shuxia Wang, Shuxin Wang, Shuya Wang, Shuye Wang, Shuyue Wang, Shuzhe Wang, Shuzhen Wang, Shuzhong Wang, Shyi-Gang P Wang, Si Wang, Sibo Wang, Sidan Wang, Sihua Wang, Sijia Wang, Silas L Wang, Silu Wang, Simeng Wang, Siqi Wang, Siqing Wang, Siwei Wang, Siyang Wang, Siyi Wang, Siying Wang, Siyu Wang, Siyuan Wang, Siyue Wang, Song Wang, Songjiao Wang, Songlin Wang, Songping Wang, Songsong Wang, Songtao Wang, Sophie H Wang, Stephani Wang, Su'e Wang, Su-Guo Wang, Su-Hua Wang, Sufang Wang, Sugai Wang, Sui Wang, Suiyan Wang, Sujie Wang, Sujuan Wang, Suli Wang, Sun Wang, Supeng Perry Wang, Suxia Wang, Suyun Wang, Suzhen Wang, T Q Wang, T Wang, T Y Wang, Taian Wang, Taicheng Wang, Taishu Wang, Tammy C Wang, Tao Wang, Taoxia Wang, Teng Wang, Tengfei Wang, Theodore Wang, Thomas T Y Wang, Tian Wang, Tian-Li Wang, Tian-Lu Wang, Tian-Tian Wang, Tian-Yi Wang, Tiancheng Wang, Tiange Wang, Tianhao Wang, Tianhu Wang, Tianhui Wang, Tianjing Wang, Tianjun Wang, Tianlin Wang, Tiannan Wang, Tianpeng Wang, Tianqi Wang, Tianqin Wang, Tianqing Wang, Tiansheng Wang, Tiansong Wang, Tiantian Wang, Tianyi Wang, Tianying Wang, Tianyuan Wang, Tielin Wang, Tienju Wang, Tieqiao Wang, Timothy C Wang, Ting Chen Wang, Ting Wang, Ting-Chen Wang, Ting-Hua Wang, Ting-Ting Wang, Tingting Wang, Tingye Wang, Tingyu Wang, Tom J Wang, Tong Wang, Tong-Hong Wang, Tongsong Wang, Tongtong Wang, Tongxia Wang, Tongxin Wang, Tongyao Wang, Tony Wang, Tzung-Dau Wang, Victoria Wang, Vivian Wang, W Wang, Wanbing Wang, Wanchun Wang, Wang Wang, Wangxia Wang, Wanliang Wang, Wanxia Wang, Wanyao Wang, Wanyi Wang, Wanyu Wang, Wayseen Wang, Wei Wang, Wei-En Wang, Wei-Feng Wang, Wei-Lien Wang, Wei-Qi Wang, Wei-Ting Wang, Wei-Wei Wang, Weicheng Wang, Weiding Wang, Weidong Wang, Weifan Wang, Weiguang Wang, Weihao Wang, Weihong Wang, Weihua Wang, Weijian Wang, Weijie Wang, Weijun Wang, Weilin Wang, Weiling Wang, Weilong Wang, Weimin Wang, Weina Wang, Weining Wang, Weipeng Wang, Weiqin Wang, Weiqing Wang, Weirong Wang, Weiwei Wang, Weiwen Wang, Weixiao Wang, Weixue Wang, Weiyan Wang, Weiyu Wang, Weiyuan Wang, Weizhen Wang, Weizhi Wang, Weizhong Wang, Wen Wang, Wen-Chang Wang, Wen-Der Wang, Wen-Fei Wang, Wen-Jie Wang, Wen-Jun Wang, Wen-Qing Wang, Wen-Xuan Wang, Wen-Yan Wang, Wen-Ying Wang, Wen-Yong Wang, Wen-mei Wang, Wenbin Wang, Wenbo Wang, Wence Wang, Wenchao Wang, Wencheng Wang, Wendong Wang, Wenfei Wang, Wengong Wang, Wenhan Wang, Wenhao Wang, Wenhe Wang, Wenhui Wang, Wenjie Wang, Wenjing Wang, Wenju Wang, Wenjuan Wang, Wenjun Wang, Wenkai Wang, Wenkang Wang, Wenke Wang, Wenming Wang, Wenqi Wang, Wenqiang Wang, Wenqing Wang, Wenran Wang, Wenrui Wang, Wentao Wang, Wentian Wang, Wenting Wang, Wenwen Wang, Wenxia Wang, Wenxian Wang, Wenxiang Wang, Wenxiu Wang, Wenxuan Wang, Wenya Wang, Wenyan Wang, Wenyi Wang, Wenying Wang, Wenyu Wang, Wenyuan Wang, Wenzhou Wang, William Wang, Won-Jing Wang, Wu-Wei Wang, Wuji Wang, Wuqing Wang, Wusan Wang, X E Wang, X F Wang, X O Wang, X S Wang, X Wang, X-T Wang, Xi Wang, Xi-Hong Wang, Xi-Rui Wang, Xia Wang, Xian Wang, Xian-e Wang, Xianding Wang, Xianfeng Wang, Xiang Wang, Xiang-Dong Wang, Xiangcheng Wang, Xiangding Wang, Xiangdong Wang, Xiangguo Wang, Xianghua Wang, Xiangkun Wang, Xiangrong Wang, Xiangru Wang, Xiangwei Wang, Xiangyu Wang, Xianna Wang, Xianqiang Wang, Xianrong Wang, Xianshi Wang, Xianshu Wang, Xiansong Wang, Xiantao Wang, Xianwei Wang, Xianxing Wang, Xianze Wang, Xianzhe Wang, Xianzong Wang, Xiao Ling Wang, Xiao Qun Wang, Xiao Wang, Xiao-Ai Wang, Xiao-Fei Wang, Xiao-Hui Wang, Xiao-Jie Wang, Xiao-Juan Wang, Xiao-Lan Wang, Xiao-Li Wang, Xiao-Lin Wang, Xiao-Ming Wang, Xiao-Pei Wang, Xiao-Qian Wang, Xiao-Qun Wang, Xiao-Tong Wang, Xiao-Xia Wang, Xiao-Yi Wang, Xiao-Yun Wang, Xiao-jian WANG, Xiao-liang Wang, Xiaobin Wang, Xiaobo Wang, Xiaochen Wang, Xiaochuan Wang, Xiaochun Wang, Xiaodan Wang, Xiaoding Wang, Xiaodong Wang, Xiaofang Wang, Xiaofei Wang, Xiaofen Wang, Xiaofeng Wang, Xiaogang Wang, Xiaohong Wang, Xiaohu Wang, Xiaohua Wang, Xiaohui Wang, Xiaojia Wang, Xiaojian Wang, Xiaojiao Wang, Xiaojie Wang, Xiaojing Wang, Xiaojuan Wang, Xiaojun Wang, Xiaokun Wang, Xiaole Wang, Xiaoli Wang, Xiaoliang Wang, Xiaolin Wang, Xiaoling Wang, Xiaolong Wang, Xiaolu Wang, Xiaolun Wang, Xiaoman Wang, Xiaomei Wang, Xiaomeng Wang, Xiaomin Wang, Xiaoming Wang, Xiaona Wang, Xiaonan Wang, Xiaoning Wang, Xiaoqi Wang, Xiaoqian Wang, Xiaoqin Wang, Xiaoqing Wang, Xiaoqiu Wang, Xiaoqun Wang, Xiaorong Wang, Xiaorui Wang, Xiaoshan Wang, Xiaosong Wang, Xiaotang Wang, Xiaoting Wang, Xiaotong Wang, Xiaowei Wang, Xiaowen Wang, Xiaowu Wang, Xiaoxia Wang, Xiaoxiao Wang, Xiaoxin Wang, Xiaoxin X Wang, Xiaoxuan Wang, Xiaoya Wang, Xiaoyan Wang, Xiaoyang Wang, Xiaoye Wang, Xiaoying Wang, Xiaoyu Wang, Xiaozhen Wang, Xiaozhi Wang, Xiaozhong Wang, Xiaozhu Wang, Xichun Wang, Xidi Wang, Xietong Wang, Xifeng Wang, Xifu Wang, Xijun Wang, Xike Wang, Xin Wang, Xin Wei Wang, Xin-Hua Wang, Xin-Liang Wang, Xin-Ming Wang, Xin-Peng Wang, Xin-Qun Wang, Xin-Shang Wang, Xin-Xin Wang, Xin-Yang Wang, Xin-Yue Wang, Xinbo Wang, Xinchang Wang, Xinchao Wang, Xinchen Wang, Xincheng Wang, Xinchun Wang, Xindi Wang, Xindong Wang, Xing Wang, Xing-Huan Wang, Xing-Jin Wang, Xing-Jun Wang, Xing-Lei Wang, Xing-Ping Wang, Xing-Quan Wang, Xingbang Wang, Xingchen Wang, Xingde Wang, Xingguo Wang, Xinghao Wang, Xinghui Wang, Xingjie Wang, Xingjin Wang, Xinglei Wang, Xinglong Wang, Xingqin Wang, Xinguo Wang, Xingxin Wang, Xingxing Wang, Xingye Wang, Xingyu Wang, Xingyue Wang, Xingyun Wang, Xinhui Wang, Xinjing Wang, Xinjun Wang, Xinke Wang, Xinkun Wang, Xinli Wang, Xinlin Wang, Xinlong Wang, Xinmei Wang, Xinqi Wang, Xinquan Wang, Xinran Wang, Xinrong Wang, Xinru Wang, Xinrui Wang, Xinshuai Wang, Xintong Wang, Xinwen Wang, Xinxin Wang, Xinyan Wang, Xinyang Wang, Xinye Wang, Xinyi Wang, Xinying Wang, Xinyu Wang, Xinyue Wang, Xinzhou Wang, Xiong Wang, Xiongjun Wang, Xiru Wang, Xitian Wang, Xiu-Lian Wang, Xiu-Ping Wang, Xiufen Wang, Xiujuan Wang, Xiujun Wang, Xiurong Wang, Xiuwen Wang, Xiuyu Wang, Xiuyuan Hugh Wang, Xixi Wang, Xixiang Wang, Xiyan Wang, Xiyue Wang, Xizhi Wang, Xu Wang, Xu-Hong Wang, Xuan Wang, Xuan-Ren Wang, Xuan-Ying Wang, Xuanwen Wang, Xuanyi Wang, Xubo Wang, Xudong Wang, Xue Wang, Xue-Feng Wang, Xue-Hua Wang, Xue-Lei Wang, Xue-Lian Wang, Xue-Rui Wang, Xue-Yao Wang, Xue-Ying Wang, Xuebin Wang, Xueding Wang, Xuedong Wang, Xuefei Wang, Xuefeng Wang, Xueguo Wang, Xuehao Wang, Xuejie Wang, Xuejing Wang, Xueju Wang, Xuejun Wang, Xuekai Wang, Xuelai Wang, Xuelian Wang, Xuelin Wang, Xuemei Wang, Xuemin Wang, Xueping Wang, Xueqian Wang, Xueqin Wang, Xuesong Wang, Xueting Wang, Xuewei Wang, Xuewen Wang, Xuexiang Wang, Xueyan Wang, Xueyi Wang, Xueying Wang, Xueyun Wang, Xuezhen Wang, Xuezheng Wang, Xufei Wang, Xujing Wang, Xuliang Wang, Xumeng Wang, Xun Wang, Xuping Wang, Xuqiao Wang, Xuru Wang, Xusheng Wang, Xv Wang, Y Alan Wang, Y B Wang, Y H Wang, Y L Wang, Y P Wang, Y Wang, Y Y Wang, Y Z Wang, Y-H Wang, Y-S Wang, Ya Qi Wang, Ya Wang, Ya Xing Wang, Ya-Han Wang, Ya-Jie Wang, Ya-Long Wang, Ya-Nan Wang, Ya-Ping Wang, Ya-Qin Wang, Ya-Zhou Wang, Yachen Wang, Yachun Wang, Yadong Wang, Yafang Wang, Yafen Wang, Yahong Wang, Yahui Wang, Yajie Wang, Yajing Wang, Yajun Wang, Yake Wang, Yakun Wang, Yali Wang, Yalin Wang, Yaling Wang, Yalong Wang, Yan Ming Wang, Yan Wang, Yan-Chao Wang, Yan-Chun Wang, Yan-Feng Wang, Yan-Ge Wang, Yan-Jiang Wang, Yan-Jun Wang, Yan-Ming Wang, Yan-Yang Wang, Yan-Yi Wang, Yan-Zi Wang, Yana Wang, Yanan Wang, Yanbin Wang, Yanbing Wang, Yanchun Wang, Yancun Wang, Yanfang Wang, Yanfei Wang, Yanfeng Wang, Yang Wang, Yang-Yang Wang, Yange Wang, Yanggan Wang, Yangpeng Wang, Yangyang Wang, Yangyufan Wang, Yanhai Wang, Yanhong Wang, Yanhua Wang, Yanhui Wang, Yani Wang, Yanjin Wang, Yanjun Wang, Yankun Wang, Yanlei Wang, Yanli Wang, Yanliang Wang, Yanlin Wang, Yanling Wang, Yanmei Wang, Yanming Wang, Yanni Wang, Yanong Wang, Yanping Wang, Yanqing Wang, Yanru Wang, Yanting Wang, Yanwen Wang, Yanxia Wang, Yanxing Wang, Yanyang Wang, Yanyun Wang, Yanzhe Wang, Yanzhu Wang, Yao Wang, Yaobin Wang, Yaochun Wang, Yaodong Wang, Yaohe Wang, Yaokun Wang, Yaoling Wang, Yaolou Wang, Yaoxian Wang, Yaoxing Wang, Yaozhi Wang, Yapeng Wang, Yaping Wang, Yaqi Wang, Yaqian Wang, Yaqiong Wang, Yaru Wang, Yatao Wang, Yating Wang, Yawei Wang, Yaxian Wang, Yaxin Wang, Yaxiong Wang, Yaxuan Wang, Yayu Wang, Yazhou Wang, Ye Wang, Ye-Ran Wang, Yefu Wang, Yeh-Han Wang, Yehan Wang, Yeming Wang, Yen-Feng Wang, Yen-Sheng Wang, Yeou-Lih Wang, Yeqi Wang, Yezhou Wang, Yi Fan Wang, Yi Lei Wang, Yi Wang, Yi-Cheng Wang, Yi-Chuan Wang, Yi-Ming Wang, Yi-Ni Wang, Yi-Ning Wang, Yi-Shan Wang, Yi-Shiuan Wang, Yi-Shu Wang, Yi-Tao Wang, Yi-Ting Wang, Yi-Wen Wang, Yi-Xin Wang, Yi-Xuan Wang, Yi-Yi Wang, Yi-Ying Wang, Yi-Zhen Wang, Yi-sheng Wang, YiLi Wang, Yian Wang, Yibin Wang, Yibing Wang, Yichen Wang, Yicheng Wang, Yichuan Wang, Yifan Wang, Yifei Wang, Yigang Wang, Yige Wang, Yihan Wang, Yihao Wang, Yihe Wang, Yijin Wang, Yijing Wang, Yijun Wang, Yikang Wang, Yike Wang, Yilin Wang, Yilu Wang, Yimeng Wang, Yiming Wang, Yin Wang, Yin-Hu Wang, Yinan Wang, Yinbo Wang, Yindan Wang, Ying Wang, Ying-Piao Wang, Ying-Wei Wang, Ying-Zi Wang, Yingbo Wang, Yingcheng Wang, Yingchun Wang, Yingfei Wang, Yingge Wang, Yinggui Wang, Yinghui Wang, Yingjie Wang, Yingmei Wang, Yingna Wang, Yingping Wang, Yingqiao Wang, Yingtai Wang, Yingte Wang, Yingwei Wang, Yingwen Wang, Yingxiong Wang, Yingxue Wang, Yingyi Wang, Yingying Wang, Yingzi Wang, Yinhuai Wang, Yining E Wang, Yinong Wang, Yinsheng Wang, Yintao Wang, Yinuo Wang, Yinxiong Wang, Yinyin Wang, Yiou Wang, Yipeng Wang, Yiping Wang, Yiqi Wang, Yiqiao Wang, Yiqin Wang, Yiqing Wang, Yiquan Wang, Yirong Wang, Yiru Wang, Yirui Wang, Yishan Wang, Yishu Wang, Yitao Wang, Yiting Wang, Yiwei Wang, Yiwen Wang, Yixi Wang, Yixian Wang, Yixuan Wang, Yiyan Wang, Yiyi Wang, Yiying Wang, Yizhe Wang, Yong Wang, Yong-Bo Wang, Yong-Gang Wang, Yong-Jie Wang, Yong-Jun Wang, Yong-Tang Wang, Yongbin Wang, Yongdi Wang, Yongfei Wang, Yongfeng Wang, Yonggang Wang, Yonghong Wang, Yongjie Wang, Yongjun Wang, Yongkang Wang, Yongkuan Wang, Yongli Wang, Yongliang Wang, Yonglun Wang, Yongmei Wang, Yongming Wang, Yongni Wang, Yongqiang Wang, Yongqing Wang, Yongrui Wang, Yongsheng Wang, Yongxiang Wang, Yongyi Wang, Yongzhong Wang, You Wang, Youhua Wang, Youji Wang, Youjie Wang, Youli Wang, Youzhao Wang, Youzhi Wang, Yu Qin Wang, Yu Tian Wang, Yu Wang, Yu'e Wang, Yu-Chen Wang, Yu-Fan Wang, Yu-Fen Wang, Yu-Hang Wang, Yu-Hui Wang, Yu-Ping Wang, Yu-Ting Wang, Yu-Wei Wang, Yu-Wen Wang, Yu-Ying Wang, Yu-Zhe Wang, Yu-Zhuo Wang, Yuan Wang, Yuan-Hung Wang, Yuanbo Wang, Yuanfan Wang, Yuanjiang Wang, Yuanli Wang, Yuanqiang Wang, Yuanqing Wang, Yuanyong Wang, Yuanyuan Wang, Yuanzhen Wang, Yubing Wang, Yubo Wang, Yuchen Wang, Yucheng Wang, Yuchuan Wang, Yudong Wang, Yue Wang, Yue-Min 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Wang, Ziyu Wang, Ziyun Wang, Zongbao Wang, Zonggui Wang, Zongji Wang, Zongkui Wang, Zongqi Wang, Zongwei Wang, Zou Wang, Zulong Wang, Zumin Wang, Zun Wang, Zunxian Wang, Zuo Wang, Zuoheng Wang, Zuoyan Wang, Zusen Wang
articles
Rashid H Osman, Long Liu, Lili Xia +8 more · 2016 · Molecular and cellular biochemistry · Springer · added 2026-04-24
Global prevalence of non-alcoholic fatty liver disease (NAFLD) constitutes a threat to human health. Goose is a unique model of NAFLD for discovering therapeutic targets as its liver can develop sever Show more
Global prevalence of non-alcoholic fatty liver disease (NAFLD) constitutes a threat to human health. Goose is a unique model of NAFLD for discovering therapeutic targets as its liver can develop severe steatosis without overt injury. Fatty acid desaturase (Fads) is a potential therapeutic target as Fads expression and mutations are associated with liver fat. Here, we hypothesized that Fads was promoted to provide a protection for goose fatty liver. To test this, goose Fads1 and Fads2 were sequenced. Fads1/2/6 expression was determined in goose liver and primary hepatocytes by quantitative PCR. Liver fatty acid composition was also analyzed by gas chromatography. Data indicated that hepatic Fads1/2/6 expression was gradually increased with the time of overfeeding. In contrast, trans-C18:1n9 fatty acid (Fads inhibitor) was reduced. However, enhanced Fads capacity for long-chain polyunsaturated fatty acid (LC-PUFA) synthesis was not sufficient to compensate for the depleted LC-PUFAs in goose fatty liver. Moreover, cell studies showed that Fads1/2/6 expression was regulated by fatty liver-associated factors. Together, these findings suggest Fads1/2 as protective components are promoted to meet instant need for LC-PUFAs in goose fatty liver, and we propose this is required for severe hepatic steatosis without liver injury. Show less
no PDF DOI: 10.1007/s11010-016-2737-7
FADS1
Si-Wei Li, Jin Wang, Ying Yang +6 more · 2016 · Journal of translational medicine · BioMed Central · added 2026-04-24
To explore whether plasma fatty acids and SNPs in the fatty acid desaturase (FADS) gene associated with type 2 diabetes (T2D) and coronary artery disease (CAD). In this cross-sectional study, we utili Show more
To explore whether plasma fatty acids and SNPs in the fatty acid desaturase (FADS) gene associated with type 2 diabetes (T2D) and coronary artery disease (CAD). In this cross-sectional study, we utilized gas chromatography-mass spectrometric analysis and the high-resolution melting method to detect plasma fatty acids and SNPs respectively (rs174537G>T, rs174616C>T, rs174460T>C, and rs174450A>C) in 234 T2D, 200 CAD, 185 T2D&CAD patients, and 253 healthy controls. We found that T2D&CAD patients had the highest plasma arachidonic acid, dihomo-gamma-linolenic acid and delta-6 desaturase, and the lowest stearic acid, linolenic acid, and saturated fatty acids; plasma eicosapentaenoic acid and docosahexaenoic acid elevated in T2D patients, but significantly reduced in CAD patients. Moreover, T2D patients with rs174537 GG genotype were at risk of developing T2D&CAD (odds ratio (OR) 1.763; 95 % CI 1.143-2.718; p = 0.010), with elevated plasma LDL-cholesterol, arachidonic acid, and delta-6 desaturase. Our results show that SNPs in FADS gene (particularly rs174537) associate with plasma fatty acids and desaturase levels in patients with both T2D and CAD, which maybe increases the risk of CAD in diabetic patients. Show less
📄 PDF DOI: 10.1186/s12967-016-0834-8
FADS1
Wen-li Song, Yu Tian, Xian-e Wang +7 more · 2016 · Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · added 2026-04-24
To investigate the potential association between FADS1 rs174537 polymorphism and serum proteins in patients with aggressive periodontitis, which may provide benefits for diagnosis and treatment of agg Show more
To investigate the potential association between FADS1 rs174537 polymorphism and serum proteins in patients with aggressive periodontitis, which may provide benefits for diagnosis and treatment of aggressive periodontitis. A total of 353 patients with aggressive periodontitis (group AgP) and 125 matched controls (group HP) were recruited in the study. Genotyping of FADS1 rs174537 and serum biochemical indexes were tested at the study's start. The relationships between the levels of TP, GLB, ALB, A/G and genotyping were analyzed. (1) The detection rate of allele G in group AgP was higher than that in group HP(68.1% vs. 61.2%, P=0.046,OR=1.35,95% CI 1.00-1.83); the detection rate of genotype GG in group AgP was higher than in group HP(45.5% vs. 34.4%,P=0.029, OR=1.60, 95% CI 1.05-2.44). (2) In group AgP, the patients with GG genotype exhibited significantly lower TP, GLB than the patients with GT+TT genotype [(77.08 ± 7.88) g/L vs. (79.00 ± 4.66) g/L, P=0.007; (28.17 ± 7.63) g/L vs.(29.88 ± 3.49) g/L,P=0.007) and the higher A/G(1.72 ± 0.22 vs.1.67 ± 0.22, P=0.040), but there was no significant difference in ALB between the patients with GG genotype and the patients with GT+TT genotype. In group HP, there were no significant differences in TP, GLB, A/G and ALB between individuals with genotype GT+TT and with genotype GG. (3)Compared with individuals with genotype GT+TT in group HP, the AgP patients with genotype GT+TT exhibited significantly higher TP, GLB [(79.00 ± 4.66) g/L vs. (75.20 ± 4.53) g/L, P<0.01; (29.88 ± 3.49) g/L vs.(26.55 ± 2.94) g/L, P<0.01) and the lower A/G(1.67 ± 0.22 vs. 1.88 ± 0.30, P<0.01), but there was no significant difference in ALB. There were no significant differences in TP, GLB, A/G and ALB the between the AgP patients with genotype GG and the healthy subjects with the same genotype either. FADS1 rs174537 polymorphism is associated with aggressive periodontitis. The patients with genotype GG in group AgP had relatively lower TP,GLB and higher A/G. Genotype GG might be a risk indicator for aggressive periodontitis by reducing host defense capability and contributing to inflammatory response in the occurrence and development of aggressive periodontitis. Show less
no PDF
FADS1
Ye Tian, Wei Zhang, Shigang Zhao +11 more · 2016 · Scientific reports · Nature · added 2026-04-24
Dyslipidemia is common in polycystic ovary syndrome (PCOS). This study was aimed to investigate whether fatty acid desaturase genes (FADS), a dyslipidemia-related gene cluster, are associated with PCO Show more
Dyslipidemia is common in polycystic ovary syndrome (PCOS). This study was aimed to investigate whether fatty acid desaturase genes (FADS), a dyslipidemia-related gene cluster, are associated with PCOS. We scanned variations of FADS genes using our previous data of genome-wide association study (GWAS) for PCOS and selected rs174570 for further study. The case-control study was conducted in an independent cohort of 1918 PCOS cases and 1889 age-matched controls and family-based study was conducted in a set of 243 core family trios with PCOS probands. Minor allele frequency (allele T) of rs174570 was significantly lower in PCOS cases than that in age-matched controls (P = 2.17E-03, OR = 0.85), even after adjustment of BMI and age. PCOS subjects carrying CC genotype had higher testosterone level and similar lipid/glucose level compared with those carrying TT or TC genotype. In trios, transmission disequilibrium test (TDT) analysis revealed risk allele C of rs174570 was significantly over-transmitted (P = 2.00E-04). Decreased expression of FADS2 was detected in PCOS cases and expression quantitative trait loci (eQTL) analysis revealed the risk allele C dosage was correlated with the decline of FADS2 expression (P = 0.002). Our results demonstrate that FADS1-FADS2 are susceptibility genes for PCOS. Show less
📄 PDF DOI: 10.1038/srep21195
FADS1
Yixuan Fan, Caifang Ren, Zhibo Wang +7 more · 2016 · Gene · Elsevier · added 2026-04-24
The n-3 fatty acid desaturase gene fat1 codes for the n-3 desaturase enzyme, which can convert n-6 polyunsaturated fatty acids (PUFAs) to n-3 PUFAs. The n-3 PUFAs are essential components required for Show more
The n-3 fatty acid desaturase gene fat1 codes for the n-3 desaturase enzyme, which can convert n-6 polyunsaturated fatty acids (PUFAs) to n-3 PUFAs. The n-3 PUFAs are essential components required for normal cellular function and have preventive and therapeutic effects on many diseases. Goat is an important domestic animal for human consumption of meat and milk. To elevate the concentrations of n-3 PUFAs and examine the regulatory mechanism of fat1 in PUFA metabolism in goat cells, we successfully constructed a humanized fat1 expression vector and confirmed the efficient expression of fat1 in goat ear skin-derived fibroblast cells (GEFCs) by qRT-PCR and Western blot analysis. Fatty acid analysis showed that fat1 overexpression significantly increased the levels of total n-3 PUFAs and decreased the levels of total n-6 PUFAs in GEFCs. In addition, qRT-PCR results indicate that the FADS1 and FADS2 desaturase genes, ELOV2 and ELOV5 elongase genes, ACO and CPT1 oxidation genes, and PPARa and PPARγ transcription factors are up-regulated, and transcription factors of SREBP-1c gene are down-regulated in the fat1 transgenic goat cells. Overall, fat1-overexpression resulted in an increase in the n-3 fatty acids and altered expression of PUFA synthesis related genes in GEFCs. This work lays a foundation for both the production of fat1 transgenic goats and further study of the mechanism of fat1 function in the PUFAs metabolism. Show less
no PDF DOI: 10.1016/j.gene.2015.10.013
FADS1
Haiying Chen, Hongli Yang, Chong Xu +8 more · 2016 · Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · Elsevier · added 2026-04-24
Pulmonary arterial hypertension (PAH) is associated with sustained vasoconstriction, inflammation and suppressed apoptosis of smooth muscle cells. Our previous studies have found that rat bone marrow- Show more
Pulmonary arterial hypertension (PAH) is associated with sustained vasoconstriction, inflammation and suppressed apoptosis of smooth muscle cells. Our previous studies have found that rat bone marrow-derived mesenchymal stem cells (rBMSCs) transduced with a mutant caveolin-1(F92A-Cav1) could enhance endothelial nitric oxide synthase (eNOS) activity and improve pulmonary vascular remodeling, but the potential mechanism is not yet fully explored. The present study was to investigate the gene expression profile upon rBMSCs/F92A-Cav1delivered to PAH rat to evaluate the role of F92A-Cav1 in its regulation. PAH was induced with monocrotaline (MCT, 60mg/kg) prior to delivery of lentiviral vector transduced rBMSCs expressing Cav1 or F92A-Cav1. Gene expression profiling was performed using Rat Signal Transduction PathwayFinder array. The expression changes of 84 key genes representing 10 signal transduction pathways in rat following rBMSCs/F92A-Cav1 treatment was examined. Screening with the Rat Signal Transduction PathwayFinder R rBMSCs/F92A-Cav1 inhibits inflammation and cell proliferation by regulating signaling pathways that related to inflammation, proliferation, cell cycle and oxidative stress. Show less
no PDF DOI: 10.1016/j.biopha.2016.06.028
HEY2
Dan-Chun Wu, Mei-Fang Zhang, Shu-Guang Su +5 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
HEY2, a bHLH transcription factor, has been implicated in the progression of human cancers. Here, we showed that HEY2 expression was markedly increased in HCC, compared with the adjacent nontumorous t Show more
HEY2, a bHLH transcription factor, has been implicated in the progression of human cancers. Here, we showed that HEY2 expression was markedly increased in HCC, compared with the adjacent nontumorous tissues. High HEY2 expression was closely correlated with tumor multiplicity, tumor differentiation and TNM stage. Kaplan-Meier analyses revealed that HEY2 expression was significantly associated with poor overall and disease-free survival in a training cohort of 361 patients with HCC. The prognostic implication of HEY2 was validated in another cohort of 169 HCC patients. Multivariate Cox regression model indicated HEY2 as an independent factor for overall survival in HCC (Hazard ratio = 1.645, 95% confident interval: 1.309-2.067, P<0.001). We also demonstrated that HEY2 expression was inhibited by miR-137. In clinical samples, HEY2 expression was reversely associated to miR-137 expression. Furthermore, overexpression of HEY2 increased cell viabilities, colony formation and cell migration, whereas knockdown of HEY2 resulted in the opposite phenotypes. Collectively, our data suggest HEY2 as a promising biomarker for unfavorable outcomes and a novel therapeutic target for the clinical management of HCC. Show less
📄 PDF DOI: 10.18632/oncotarget.9343
HEY2
Lai Man Natalie Wu, Jincheng Wang, Andrea Conidi +12 more · 2016 · Nature neuroscience · Nature · added 2026-04-24
The mechanisms that coordinate and balance a complex network of opposing regulators to control Schwann cell (SC) differentiation remain elusive. Here we demonstrate that zinc-finger E-box-binding home Show more
The mechanisms that coordinate and balance a complex network of opposing regulators to control Schwann cell (SC) differentiation remain elusive. Here we demonstrate that zinc-finger E-box-binding homeobox 2 (Zeb2, also called Sip1) transcription factor is a critical intrinsic timer that controls the onset of SC differentiation by recruiting histone deacetylases HDAC 1 and 2 (HDAC1/2) and nucleosome remodeling and deacetylase complex (NuRD) co-repressor complexes in mice. Zeb2 deletion arrests SCs at an undifferentiated state during peripheral nerve development and inhibits remyelination after injury. Zeb2 antagonizes inhibitory effectors including Notch and Sox2. Importantly, genome-wide transcriptome analysis reveals a Zeb2 target gene encoding the Notch effector Hey2 as a potent inhibitor for Schwann cell differentiation. Strikingly, a genetic Zeb2 variant associated with Mowat-Wilson syndrome disrupts the interaction with HDAC1/2-NuRD and abolishes Zeb2 activity for SC differentiation. Therefore, Zeb2 controls SC maturation by recruiting HDAC1/2-NuRD complexes and inhibiting a Notch-Hey2 signaling axis, pointing to the critical role of HDAC1/2-NuRD activity in peripheral neuropathies caused by ZEB2 mutations. Show less
📄 PDF DOI: 10.1038/nn.4322
HEY2
Timothy Ht Cheng, Deborah J Thompson, Tracy A O'Mara +89 more · 2016 · Nature genetics · Nature · added 2026-04-24
Timothy Ht Cheng, Deborah J Thompson, Tracy A O'Mara, Jodie N Painter, Dylan M Glubb, Susanne Flach, Annabelle Lewis, Juliet D French, Luke Freeman-Mills, David Church, Maggie Gorman, Lynn Martin, National Study of Endometrial Cancer Genetics Group (NSECG), Shirley Hodgson, Penelope M Webb, Australian National Endometrial Cancer Study Group (ANECS), John Attia, Elizabeth G Holliday, Mark McEvoy, Rodney J Scott, Anjali K Henders, Nicholas G Martin, Grant W Montgomery, Dale R Nyholt, Shahana Ahmed, Catherine S Healey, Mitul Shah, Joe Dennis, Peter A Fasching, Matthias W Beckmann, Alexander Hein, Arif B Ekici, Per Hall, Kamila Czene, Hatef Darabi, Jingmei Li, Thilo Dörk, Matthias Dürst, Peter Hillemanns, Ingo Runnebaum, Frederic Amant, Stefanie Schrauwen, Hui Zhao, Diether Lambrechts, Jeroen Depreeuw, Sean C Dowdy, Ellen L Goode, Brooke L Fridley, Stacey J Winham, Tormund S Njølstad, Helga B Salvesen, Jone Trovik, Henrica Mj Werner, Katie Ashton, Geoffrey Otton, Tony Proietto, Tao Liu, Miriam Mints, Emma Tham, RENDOCAS, Chibcha Consortium, Mulin Jun Li, Shun H Yip, Junwen Wang, Manjeet K Bolla, Kyriaki Michailidou, Qin Wang, Jonathan P Tyrer, Malcolm Dunlop, Richard Houlston, Claire Palles, John L Hopper, AOCS Group, Julian Peto, Anthony J Swerdlow, Barbara Burwinkel, Hermann Brenner, Alfons Meindl, Hiltrud Brauch, Annika Lindblom, Jenny Chang-Claude, Fergus J Couch, Graham G Giles, Vessela N Kristensen, Angela Cox, Julie M Cunningham, Paul D P Pharoah, Alison M Dunning, Stacey L Edwards, Douglas F Easton, Ian Tomlinson, Amanda B Spurdle Show less
We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestr Show more
We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer. Show less
📄 PDF DOI: 10.1038/ng.3562
HEY2
Niek Verweij, Irene Mateo Leach, Aaron Isaacs +27 more · 2016 · Human molecular genetics · Oxford University Press · added 2026-04-24
The ST-segment and adjacent T-wave (ST-T wave) amplitudes of the electrocardiogram are quantitative characteristics of cardiac repolarization. Repolarization abnormalities have been linked to ventricu Show more
The ST-segment and adjacent T-wave (ST-T wave) amplitudes of the electrocardiogram are quantitative characteristics of cardiac repolarization. Repolarization abnormalities have been linked to ventricular arrhythmias and sudden cardiac death. We performed the first genome-wide association meta-analysis of ST-T-wave amplitudes in up to 37 977 individuals identifying 71 robust genotype-phenotype associations clustered within 28 independent loci. Fifty-four genes were prioritized as candidates underlying the phenotypes, including genes with established roles in the cardiac repolarization phase (SCN5A/SCN10A, KCND3, KCNB1, NOS1AP and HEY2) and others with as yet undefined cardiac function. These associations may provide insights in the spatiotemporal contribution of genetic variation influencing cardiac repolarization and provide novel leads for future functional follow-up. Show less
📄 PDF DOI: 10.1093/hmg/ddw058
HEY2
Xiao-Feng Sun, Xing-Hong Sun, Shun-Feng Cheng +7 more · 2016 · Reproduction, fertility, and development · added 2026-04-24
The Notch and transforming growth factor (TGF)-β signalling pathways play an important role in granulosa cell proliferation. However, the mechanisms underlying the cross-talk between these two signall Show more
The Notch and transforming growth factor (TGF)-β signalling pathways play an important role in granulosa cell proliferation. However, the mechanisms underlying the cross-talk between these two signalling pathways are unknown. Herein we demonstrated a functional synergism between Notch and TGF-β signalling in the regulation of preantral granulosa cell (PAGC) proliferation. Activation of TGF-β signalling increased hairy/enhancer-of-split related with YRPW motif 2 gene (Hey2) expression (one of the target genes of the Notch pathway) in PAGCs, and suppression of TGF-β signalling by Smad3 knockdown reduced Hey2 expression. Inhibition of the proliferation of PAGCs by N-[N-(3,5-difluorophenacetyl)-l-alanyl]-S-phenylglycine t-butylester (DAPT), an inhibitor of Notch signalling, was rescued by both the addition of ActA and overexpression of Smad3, indicating an interaction between the TGF-β and Notch signalling pathways. Co-immunoprecipitation (CoIP) and chromatin immunoprecipitation (ChIP) assays were performed to identify the point of interaction between the two signalling pathways. CoIP showed direct protein-protein interaction between Smad3 and Notch2 intracellular domain (NICD2), whereas ChIP showed that Smad3 could be recruited to the promoter regions of Notch target genes as a transcription factor. Therefore, the findings of the present study support the idea that nuclear Smad3 protein can integrate with NICD2 to form a complex that acts as a transcription factor to bind specific DNA motifs in Notch target genes, such as Hey1 and Hey2, and thus participates in the transcriptional regulation of Notch target genes, as well as regulation of the proliferation of PAGCs. Show less
no PDF DOI: 10.1071/RD14398_CO
HEY2
Yiyan Wang, Kaiming Yuan, Xiaoheng Li +6 more · 2016 · Growth factors (Chur, Switzerland) · Taylor & Francis · added 2026-04-24
Leukemia inhibitory factor (LIF) has many physiological roles. However, its effects on Leydig cell development are still unclear. Rat immature and adult Leydig cells were cultured with different conce Show more
Leukemia inhibitory factor (LIF) has many physiological roles. However, its effects on Leydig cell development are still unclear. Rat immature and adult Leydig cells were cultured with different concentrations of LIF alone or in combination with luteinizing hormone (LH) for 24 h. LIF (1 and 10 ng/ml) significantly increased androgen production in immature Leydig cells, but had no effects on testosterone production in adult Leydig cells. Further studies revealed that LIF dose-dependently increased Star and Hsd17b3 expression levels in immature Leydig cells. Gene microarray revealed that the upregulation of anti-oxidative genes and Star might contribute to LIF-induced androgen production. In conclusion, LIF has stimulatory effects on androgen production in rat immature Leydig cells. Show less
no PDF DOI: 10.1080/08977194.2016.1183199
HSD17B12
J Wang, T Le, R Wei +1 more · 2016 · Cellular and molecular biology (Noisy-le-Grand, France) · added 2026-04-24
J Wang, T Le, R Wei, Y Jiao Show less
MicroRNAs have been shown to be closely related to many neurodegenerative disorders. The present study focuses on the role of hsa-miR-590-3p and its function in Parkinson's disease (PD). Our study sho Show more
MicroRNAs have been shown to be closely related to many neurodegenerative disorders. The present study focuses on the role of hsa-miR-590-3p and its function in Parkinson's disease (PD). Our study showed a remarkable down-regulation of miR-590-3p expression in the 1-methyl-4 phenylpyridinium (MPP+)-treated MES23.5 and SH-SY5Y cells. Furthermore, JMJD1C was identified as a target gene of miR-590-3p in humans via the luciferase reporter assay. Our study also demonstrated that up-regulation of miR-590-3p and knockdown of JMJD1C increased the expression of peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) and the downstream targets of PGC-1α, including nuclear respiratory factor 1 (NRF-1) and mitochondrial transcription factor A (TFAM), which are the key genes regulating mitochondrial function. Also, the expression of heme oxygenase-1 (HO-1), NAD (P) H quinone oxidoreductase-1 (NQO-1) and γ-glutamylcysteine synthetase (γ-GCS) involved in anti-oxidation was increased. Moreover, there was a significant increase in the total cellular ATP with an associated decrease in levels of ROS in the absence of JMJD1C. Taken together, these results show that miR-590-3p plays an important role in the pathogenesis of PD, which may be further regarded as a therapeutic target. Show less
no PDF
JMJD1C
G Jun, C A Ibrahim-Verbaas, M Vronskaya +115 more · 2016 · Molecular psychiatry · Nature · added 2026-04-24
APOE ɛ4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics o Show more
APOE ɛ4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) Consortium in APOE ɛ4+ (10 352 cases and 9207 controls) and APOE ɛ4- (7184 cases and 26 968 controls) subgroups as well as in the total sample testing for interaction between a single-nucleotide polymorphism (SNP) and APOE ɛ4 status. Suggestive associations (P<1 × 10(-4)) in stage 1 were evaluated in an independent sample (stage 2) containing 4203 subjects (APOE ɛ4+: 1250 cases and 536 controls; APOE ɛ4-: 718 cases and 1699 controls). Among APOE ɛ4- subjects, novel genome-wide significant (GWS) association was observed with 17 SNPs (all between KANSL1 and LRRC37A on chromosome 17 near MAPT) in a meta-analysis of the stage 1 and stage 2 data sets (best SNP, rs2732703, P=5·8 × 10(-9)). Conditional analysis revealed that rs2732703 accounted for association signals in the entire 100-kilobase region that includes MAPT. Except for previously identified AD loci showing stronger association in APOE ɛ4+ subjects (CR1 and CLU) or APOE ɛ4- subjects (MS4A6A/MS4A4A/MS4A6E), no other SNPs were significantly associated with AD in a specific APOE genotype subgroup. In addition, the finding in the stage 1 sample that AD risk is significantly influenced by the interaction of APOE with rs1595014 in TMEM106B (P=1·6 × 10(-7)) is noteworthy, because TMEM106B variants have previously been associated with risk of frontotemporal dementia. Expression quantitative trait locus analysis revealed that rs113986870, one of the GWS SNPs near rs2732703, is significantly associated with four KANSL1 probes that target transcription of the first translated exon and an untranslated exon in hippocampus (P ⩽ 1.3 × 10(-8)), frontal cortex (P ⩽ 1.3 × 10(-9)) and temporal cortex (P⩽1.2 × 10(-11)). Rs113986870 is also strongly associated with a MAPT probe that targets transcription of alternatively spliced exon 3 in frontal cortex (P=9.2 × 10(-6)) and temporal cortex (P=2.6 × 10(-6)). Our APOE-stratified GWAS is the first to show GWS association for AD with SNPs in the chromosome 17q21.31 region. Replication of this finding in independent samples is needed to verify that SNPs in this region have significantly stronger effects on AD risk in persons lacking APOE ɛ4 compared with persons carrying this allele, and if this is found to hold, further examination of this region and studies aimed at deciphering the mechanism(s) are warranted. Show less
📄 PDF DOI: 10.1038/mp.2015.23
KANSL1
Xiu-Min Lu, Jing-Xiang Wei, Lan Xiao +2 more · 2016 · Current pharmaceutical design · Bentham Science · added 2026-04-24
In the injured adult mammalian central nervous system (CNS), the failure of axonal regeneration is thought to be attributed, at least in part, to various myelin-associated inhibitors (MAIs), such as N Show more
In the injured adult mammalian central nervous system (CNS), the failure of axonal regeneration is thought to be attributed, at least in part, to various myelin-associated inhibitors (MAIs), such as Nogo, myelinassociated glycoprotein (MAG), and oligodendrocyte-myelin glycoprotein (OMgp) around the damaged site. Interestingly, these three structurally different inhibitors share two common receptors, Nogo-66 receptor (NgR) and paired immunoglobulin-like receptor B (PirB), and transduce the inhibitory signal into neurons via their complex combinant and co-receptors, such as p75 neurotrophin receptor (p75NTR), Nogo receptor-interacting protein 1 (LINGO-1), and TROY. Accordingly, targeting of the whole myelin or just portions by immunization has been proved to be neuroprotective and is able to promote regeneration in the injured spinal cords. In the past few years, vaccine approaches were initially achieved and could induce the production of antibodies against inhibitors in myelin to block the inhibitory effects and promote functional recovery in spinal cord injury (SCI) models by immunizing with MAIs, such as purified myelin, spinal cord homogenates, or their receptors with the concept of protective autoimmunity formulated. However, for safety consideration, further work is necessary before the immunotherapy strategies can be adopted to treat human injured spinal cords. Show less
no PDF DOI: 10.2174/1381612822666151204000855
LINGO1
Jue Wang, Zhizhong Ye, Shuhui Zheng +4 more · 2016 · Brain research · Elsevier · added 2026-04-24
Determination of the exogenous factors that regulate differentiation of neural stem/progenitor cells into neurons, oligodendrocytes and astrocytes is an important step in the clinical therapy of spina Show more
Determination of the exogenous factors that regulate differentiation of neural stem/progenitor cells into neurons, oligodendrocytes and astrocytes is an important step in the clinical therapy of spinal cord injury (SCI). The Notch pathway inhibits the differentiation of neural stem/progenitor cells and Lingo-1 is a strong negative regulator for myelination and axon growth. While Lingo-1 shRNA and N-[N-(3, 5-difluorophenacetyl)-1-alanyl]-S-Phenylglycinet-butylester (DAPT), a Notch pathway inhibitor, have been used separately to help repair SCI, the results have been unsatisfactory. Here we investigated and elucidated the preliminary mechanism for the effect of Lingo-1 shRNA and DAPT on neural stem/progenitor cells differentiation. We found that neural stem/progenitor cells from E14 rat embryos expressed Nestin, Sox-2 and Lingo-1, and we optimized the transduction of neural stem/progenitor cells using lentiviral vectors encoding Lingo-1 shRNA. The addition of DAPT decreased the expression of Notch intracellular domain (NICD) as well as the downstream genes Hes1 and Hes5. Expression of NeuN, CNPase and GFAP in DAPT treated cells and expression of NeuN in Lingo-1 shRNA treated cells confirmed differentiation of neural stem/progenitor cells into neurons, oligodendrocytes and astrocytes. These results revealed that while Lingo-1 shRNA and Notch signaling inhibitor DAPT both promoted differentiation of neural stem cells into neurons, only DAPT was capable of driving neural stem/progenitor cells differentiation into oligodendrocytes and astrocytes. Since we were able to show that both Lingo-1 shRNA and DAPT could drive neural stem/progenitor cells differentiation, our data might aid the development of more effective SCI therapies using Lingo-1 shRNA and DAPT. Show less
no PDF DOI: 10.1016/j.brainres.2015.11.029
LINGO1
Ningning Chen, Jing-Sheng Cen, Jingnan Wang +7 more · 2016 · Critical care medicine · added 2026-04-24
Leucine-rich repeat and immunoglobulin domain-containing protein (LINGO)-1 is expressed in neural stem cells, and its neutralization results in sustained neuronal immaturity. Thus, targeted inhibition Show more
Leucine-rich repeat and immunoglobulin domain-containing protein (LINGO)-1 is expressed in neural stem cells, and its neutralization results in sustained neuronal immaturity. Thus, targeted inhibition of LINGO-1 via RNA interference may enhance transplanted neural stem cell survival and neuronal differentiation in vivo. Furthermore, LINGO-1 RNA interference in neural stem cells represents a potential therapeutic strategy for spinal cord injury. Department of Spine Surgery, First Affiliated Hospital of Sun Yat-sen University. Translational Medicine Center Research Laboratory, First Affiliated Hospital of Sun Yat-sen University. Female Sprague-Dawley rats. The animals were divided into three groups that underwent laminectomy and complete spinal cord transection accompanied by transplantation of control-RNA interference-treated or LINGO-1-RNA interference-treated neural stem cells at the injured site in vivo. In vitro, neural stem cells were divided into four groups for the following treatments: control, control RNA interference lentivirus, LINGO-1 RNA interference lentivirus and LINGO-1 complementary DNA lentivirusand the Key Projects of the Natural Science Foundation of Guangdong Province (No. S2013020012818). Neural stem cells in each treatment group were examined for cell survival and neuronal differentiation in vitro and in vivo via immunofluorescence and Western blot analysis. Axonal regeneration and tissue repair were assessed via retrograde tracing using Fluorogold, electron microscopy, hematoxylin-eosin staining and MRI. Rats were also examined for functional recovery based on the measurement of spinal cord-evoked potentials and the Basso-Beattie-Bresnahan score. LINGO-1-RNA interference-treated neural stem cell transplantation increased tissue repair and functional recovery of the injured spinal cord in rats. Similarly, LINGO-1 RNA interference increased neural stem cell survival and neuronal differentiation in vitro. The mechanism underlying the effect of LINGO-1 RNA interference on the injured rat spinal cord may be that the significant inhibition of LINGO-1 expression in neural stem cells inactivated the RhoA and Notch signaling pathways, which act downstream of LINGO-1. Our findings indicate that transplantation of LINGO-1-RNA interference-treated neural stem cells facilitates functional recovery after spinal cord injury and represents a promising potential strategy for the repair of spinal cord injury. Show less
no PDF DOI: 10.1097/CCM.0000000000001351
LINGO1
Clint L Miller, Milos Pjanic, Ting Wang +17 more · 2016 · Nature communications · Nature · added 2026-04-24
Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies have identified > Show more
Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies have identified >150 loci associated with CAD and myocardial infarction susceptibility in humans. A majority of these variants reside in non-coding regions and are co-inherited with hundreds of candidate regulatory variants, presenting a challenge to elucidate their functions. Herein, we use integrative genomic, epigenomic and transcriptomic profiling of perturbed human coronary artery smooth muscle cells and tissues to begin to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps, we prioritize 64 candidate variants and perform allele-specific binding and expression analyses at seven top candidate loci: 9p21.3, SMAD3, PDGFD, IL6R, BMP1, CCDC97/TGFB1 and LMOD1. We validate our findings in expression quantitative trait loci cohorts, which together reveal new links between CAD associations and regulatory function in the appropriate disease context. Show less
📄 PDF DOI: 10.1038/ncomms12092
LMOD1
Wenxiu Ning, Yanan Yu, Honglin Xu +5 more · 2016 · Developmental cell · Elsevier · added 2026-04-24
For adaptation to complex cellular functions, dynamic cytoskeletal networks are required. There are two major components of the cytoskeleton, microtubules and actin filaments, which form an intricate Show more
For adaptation to complex cellular functions, dynamic cytoskeletal networks are required. There are two major components of the cytoskeleton, microtubules and actin filaments, which form an intricate network maintaining an exquisite cooperation to build the physical basis for their cellular function. However, little is known about the molecular mechanism underlying their synergism. Here, we show that in Caco2 epithelial cells, noncentrosomal microtubules crosstalk with F-actin through their minus ends and contribute to the regulation of focal adhesion size and cell migration. We demonstrate that ACF7, a member of the spectraplakin family of cytoskeletal crosslinking proteins, interacts with Nezha (also called CAMSAP3) at the minus ends of noncentrosomal microtubules and anchors them to actin filaments. Those noncentrosomal microtubules cooperate with actin filaments through retrograde flow to keep their length and orientation perpendicular to the cell edge as well as regulate focal adhesion size and cell migration. Show less
no PDF DOI: 10.1016/j.devcel.2016.09.003
MACF1
Dechang Diao, Lei Wang, Jin Wan +6 more · 2016 · BMC cancer · BioMed Central · added 2026-04-24
Mitogen/extracellular signal-regulated kinase kinase-5 (MEK5) has been confirmed to play a pivotal role in tumor carcinogenesis and progression. However, few studies have investigated the role of MEK5 Show more
Mitogen/extracellular signal-regulated kinase kinase-5 (MEK5) has been confirmed to play a pivotal role in tumor carcinogenesis and progression. However, few studies have investigated the role of MEK5 in colorectal cancer (CRC). MEK5 expression was determined by immunohistochemistry (IHC) in tissue microarrays (TMAs) containing 2 groups of tissues, and western blotting was used to confirm MEK5 expression in 8 cases of primary CRC tissues and paired normal mucosa. RNA interference was used to verify the biological function of MEK5 gene in the development of CRC. IHC revealed the expression of MEK5 was higher in tumor tissues (38.1 %), compared with adjacent normal tissue (8.3 %). Western blot showed that, MEK5 expression was upregulated in CRC tumor tissues compared with normal tissue. Analysis of clinical pathology parameters indicated MEK5 overexpression was significantly correlated with the depth of invasion, lymph node metastasis, distant metastasis and histological grade. Survival analysis revealed that MEK5 overexpression negatively correlated with cancer-free survival (hazard ratio 1.64, P = 0.017). RNA interference-mediated knockdown of MEK5 in SW480 colon cancer cells decreased their proliferation, division, migration and invasiveness in vitro and slowed down tumors growth in mice engrafted with the cells. MEK5 plays an important role in CRC progression and may be a potential molecular target for the treatment of CRC. Show less
📄 PDF DOI: 10.1186/s12885-016-2327-9
MAP2K5
Hai-Jun Wang, Anke Hinney, Jie-Yun Song +7 more · 2016 · BMC medical genetics · BioMed Central · added 2026-04-24
Large-scale genome-wide association studies have identified multiple genetic variants that are associated with elevated body mass index (BMI) or the risk of obesity in Caucasian or Asian populations. Show more
Large-scale genome-wide association studies have identified multiple genetic variants that are associated with elevated body mass index (BMI) or the risk of obesity in Caucasian or Asian populations. We examined whether these variants are individually associated with obesity in Chinese children, and also assessed their cumulative effects and predictive value for obesity risk in Chinese children. We genotyped 40 single nucleotide polymorphisms (SNPs) and conducted association analyses for 32/40 SNPs with an estimated minor allele frequency >1% in 2 030 unrelated Chinese children, including 607 normal-weight, 718 overweight, and 705 obese individuals from two cross-sectional study groups. Logistic regression and linear regression under the additive model were used to examine associations, and the area under the receiver operating characteristic curve (AUCROC) was reported as prediction summary. We identified obesity association for 6 SNPs near SEC16B, RBJ, CDKAL1, TFAP2B, MAP2K5 and FTO (odds ratios (ORs) ranged from 1.19 to 1.41, nominal two-sided P-values < 0.05). Association (Bonferroni corrected) of rs543874 near SEC16B and rs2241423 near MAP2K5 had presumably stronger effects on obesity in Chinese children than in Caucasian populations. Their risk alleles were also associated with BMI standard deviation score (BMI-SDS) variability. We demonstrated the cumulative effects of the 32 SNPs on obesity risk (per risk allele: OR = 1.06, 95 % CI: 1.03-1.11, P = 4.84 × 10(-4)) and BMI-SDS (β = 0.04, 95% CI: 0.02-0.06, P = 3.69 × 10(-7)). The difference in AUCROC for a model with covariates (age, age square, sex and study group) and the model including covariates and all 32 SNPs was 2.8% (P = 0.0002). While six SNPs were individually associated with obesity in Chinese children, the 32 common variants identified by recent GWA studies had cumulative effects and resulted in a limited increase in the AUCROC predictive value for childhood obesity. Show less
📄 PDF DOI: 10.1186/s12881-016-0268-4
MAP2K5
Jong-Ling Fuh, Ming-Yi Chung, Shu-Chih Yao +9 more · 2016 · Cephalalgia : an international journal of headache · SAGE Publications · added 2026-04-24
Objective Several genetic variants have been found to increase the risk of restless legs syndrome (RLS). The aim of the present study was to determine if these genetic variants were also associated wi Show more
Objective Several genetic variants have been found to increase the risk of restless legs syndrome (RLS). The aim of the present study was to determine if these genetic variants were also associated with the comorbidity of RLS and migraine in patients. Methods Thirteen single-nucleotide polymorphisms (SNPs) at six RLS risk loci ( MEIS1, BTBD9, MAP2K5, PTPRD, TOX3, and an intergenic region on chromosome 2p14) were genotyped in 211 migraine patients with RLS and 781 migraine patients without RLS. Association analyses were performed for the overall cohort, as well as for the subgroups of patients who experienced migraines with and without aura and episodic migraines (EMs) vs. chronic migraines (CMs). In order to verify which genetic markers were potentially related to the incidence of RLS in migraine patients, multivariate regression analyses were also performed. Results Among the six tested loci, only MEIS1 was significantly associated with RLS. The most significant SNP of MEIS1, rs2300478, increased the risk of RLS by 1.42-fold in the overall cohort ( p = 0.0047). In the subgroup analyses, MEIS1 augmented the risk of RLS only in the patients who experienced EMs (odds ratio (OR) = 1.99, p = 0.0004) and not those experiencing CMs. Multivariate regression analyses further showed that rs2300478 in MEIS1 (OR = 1.39, p = 0.018), a CM diagnosis (OR = 1.52, p = 0.022), and depression (OR = 1.86, p = 0.005) were independent predictors of RLS in migraine. Conclusions MEIS1 variants were associated with an increased risk of RLS in migraine patients. It is possible that an imbalance in iron homeostasis and the dopaminergic system may represent a link between RLS incidence and migraines. Show less
no PDF DOI: 10.1177/0333102415620907
MAP2K5
Mi-Sung Kim, Sarah A Krawczyk, Ludivine Doridot +10 more · 2016 · The Journal of clinical investigation · added 2026-04-24
Obese, insulin-resistant states are characterized by a paradoxical pathogenic condition in which the liver appears to be selectively insulin resistant. Specifically, insulin fails to suppress glucose Show more
Obese, insulin-resistant states are characterized by a paradoxical pathogenic condition in which the liver appears to be selectively insulin resistant. Specifically, insulin fails to suppress glucose production, yet successfully stimulates de novo lipogenesis. The mechanisms underlying this dysregulation remain controversial. Here, we hypothesized that carbohydrate-responsive element-binding protein (ChREBP), a transcriptional activator of glycolytic and lipogenic genes, plays a central role in this paradox. Administration of fructose increased hepatic hexose-phosphate levels, activated ChREBP, and caused glucose intolerance, hyperinsulinemia, hypertriglyceridemia, and hepatic steatosis in mice. Activation of ChREBP was required for the increased expression of glycolytic and lipogenic genes as well as glucose-6-phosphatase (G6pc) that was associated with the effects of fructose administration. We found that fructose-induced G6PC activity is a major determinant of hepatic glucose production and reduces hepatic glucose-6-phosphate levels to complete a homeostatic loop. Moreover, fructose activated ChREBP and induced G6pc in the absence of Foxo1a, indicating that carbohydrate-induced activation of ChREBP and G6PC dominates over the suppressive effects of insulin to enhance glucose production. This ChREBP/G6PC signaling axis is conserved in humans. Together, these findings support a carbohydrate-mediated, ChREBP-driven mechanism that contributes to hepatic insulin resistance. Show less
no PDF DOI: 10.1172/JCI81993
MLXIPL
Hongxiang Zeng, Hao Gu, Chiqi Chen +9 more · 2016 · Oncotarget · Impact Journals · added 2026-04-24
Targeting leukemia-initiating cells (LICs) is the key to eradicating leukemia and preventing its relapse. Recent studies have indicated that metabolic regulation may play a critical role in the mainte Show more
Targeting leukemia-initiating cells (LICs) is the key to eradicating leukemia and preventing its relapse. Recent studies have indicated that metabolic regulation may play a critical role in the maintenance of stemness in LICs, although the detailed mechanisms are poorly understood. Herein, we provide intriguing evidence showing that a glucose-responsive transcription factor, carbohydrate responsive element binding protein (ChREBP), served as a tumor suppressor rather than an oncogene, as previously described, to inhibit the development of acute myeloid leukemia by promoting the differentiation of LICs. Using an MLL-AF9-induced murine leukemia model, we demonstrated that the deletion of ChREBP resulted in the blockage of the differentiation of LICs and significantly reduced survival in ChREBP-null leukemic mice. However, ChREBP was not required for the normal repopulation abilities of hematopoietic stem cells. ChREBP promoted leukemia cell differentiation through the direct inhibition of RUNX1 or the transactivation of TXNIP to downregulate the RUNX1 level and ROS generation. Moreover, knockdown of ChREBP in human leukemia THP1 cells led to markedly enhanced proliferation and decreased differentiation upon PMA treatment. Collectively, we unraveled an unexpected role of ChREBP in leukemogenesis, which may provide valuable clues for developing novel metabolic strategies for leukemia treatment. Show less
📄 PDF DOI: 10.18632/oncotarget.9520
MLXIPL
Li Liu, Shang Wang, Ling Yao +6 more · 2016 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
Dietary fructose is considered a risk factor for metabolic disorders, such as fatty liver disease. However, the mechanism underlying the effects of fructose is not well characterized. We investigated Show more
Dietary fructose is considered a risk factor for metabolic disorders, such as fatty liver disease. However, the mechanism underlying the effects of fructose is not well characterized. We investigated the hepatic expression of key regulatory genes related to lipid metabolism following fructose feeding under well-defined conditions. Rats were fed standard chow supplemented with 10% w/v fructose solution for 5 weeks, and killed after chow-fasting and fructose withdrawal (fasting) or chow-fasting and continued fructose (fructose alone) for 14 h. Hepatic deposition of triglycerides was found in rats from both groups. As expected, fructose alone increased mRNA levels of lipogenesis-related genes and correspondingly decreased mRNA levels of lipid oxidative genes in the liver. Interesting, hepatic levels of stearoyl-CoA desaturase (SCD)1 mRNA remained elevated under fructose withdrawn conditions, although expression levels of other genes, including two key transcription factors (carbohydrate response element binding protein (ChREBP) and sterol regulatory element-binding protein (SREBP)-1c) fell to normal levels, indicating that long-term fructose intake increased SCD1 activity, independent of upstream regulatory genes, such as ChREBP and SREBP-1c. In conclusion, SCD1 overexpression in fatty liver disease is not affected by fasting after long-term fructose consumption in rats. Regulation of SCD1 plays an important role in fructose-induced hepatic steatosis. Show less
no PDF DOI: 10.1016/j.bbrc.2016.09.160
MLXIPL
Jiajia Gao, Xueping Qiu, Xuebin Wang +2 more · 2016 · PloS one · PLOS · added 2026-04-24
Age, gender, diet, gene and lifestyle have been reported to affect metabolic status and disease susceptibility through epigenetic pathway. But it remains indistinct that which factors account for cert Show more
Age, gender, diet, gene and lifestyle have been reported to affect metabolic status and disease susceptibility through epigenetic pathway. But it remains indistinct that which factors account for certain epigenetic modifications. Our aim was to identify the influencing factors on inter-individual DNA methylation variations of carbohydrate response element binding protein (ChREBP) and global genome in peripheral blood leucocytes (PBLs). ChREBP DNA methylation was determined by bisulfite sequencing, and genomic 5mdC contents were quantified by capillary hydrophilic-interaction liquid chromatography/ in-source fragmentation/ tandem mass spectrometry system in about 300 healthy individuals. Eleven single nucleotide polymorphisms (SNPs) spanning ChREBP and DNA methyltransferase 1 (DNMT1) were genotyped by high resolution melting or PCR-restriction fragment length polymorphism. DNMT1 mRNA expression was analyzed by quantitative PCR. We found ChREBP DNA methylation levels were statistically associated with age (Beta (B) = 0.028, p = 0.006) and serum total cholesterol concentrations (TC) (B = 0.815, p = 0.010), independent of sex, concentrations of triglyceride, high density lipoprotein cholesterol, low density lipoprotein cholesterol (LDL-C), fasting blood glucose and systolic blood pressure, diastolic blood pressure, PBLs counts and classifications. The DNMT1 haplotypes were related to ChREBP (odds ratio (OR) = 0.668, p = 0.029) and global (OR = 0.450, p = 0.015) DNA methylation as well as LDL-C, but not DNMT1 expression. However, only the relation to LDL-C was robust to correction for multiple testing (ORFDR = 1.593, pFDR = 0.013). These results indicated that the age and TC were independent influential factors of ChREBP methylation and DNMT1 variants could probably influence LDL-C to further modify ChREBP DNA methylation. Certainly, sequential comprehensive analysis of the interactions between genetic variants and blood lipid levels on ChREBP and global DNA methylation was required. Show less
📄 PDF DOI: 10.1371/journal.pone.0157128
MLXIPL
LiLi Gao, Wen Shan, Wenjing Zeng +10 more · 2016 · Molecular nutrition & food research · Wiley · added 2026-04-24
Carnosic acid (CA), which is extracted from rosemary, displays multiple pharmacological activities. This study aimed to investigate the effects of CA on chronic alcoholic liver injury and to elucidate Show more
Carnosic acid (CA), which is extracted from rosemary, displays multiple pharmacological activities. This study aimed to investigate the effects of CA on chronic alcoholic liver injury and to elucidate the related mechanisms. An in vivo rat model was established by feeding rats a liquid diet containing ethanol, and an in vitro model was created by treating HepG2 cells with 100 mM ethanol for 48 h. In the rat model of alcohol-induced liver injury, CA significantly decreased serum aminotransferase, triglyceride and total cholesterol levels. Additionally, CA inhibited oxidative stress, inflammation, and cell death. Interestingly, CA activated SIRT1, which was associated with the downregulation of lipoprotein carbohydrate response element-binding protein (ChREBP) and growth factor adapter protein (p66shc). In HepG2 cells, ethanol-induced cell injury was associated with decreased SIRT1 and increased ChREBP and p66shc protein expression. These changes were reversed by CA but enhanced by a specific SIRT1 inhibitor, EX527. Moreover, the effects of CA on SIRT1, ChREBP, and p66shc were abolished by SIRT1 siRNA or EX527, indicating that CA decreased ChREBP and p66shc expression via SIRT1 activation. CA exerted protective effects against alcoholic liver injury by activating the SIRT1/ChREBP and SIRT1/p66shc pathways, which are related to the anti-steatosis, anti-oxidant, and anti-apoptosis effects. Show less
no PDF DOI: 10.1002/mnfr.201500878
MLXIPL
Ruiyang Zhang, Congle Shen, Lijun Zhao +4 more · 2016 · International journal of cancer · Wiley · added 2026-04-24
Integration of human papillomavirus (HPV) viral DNA into the human genome has been postulated as an important etiological event during cervical carcinogenesis. Several recent reports suggested a possi Show more
Integration of human papillomavirus (HPV) viral DNA into the human genome has been postulated as an important etiological event during cervical carcinogenesis. Several recent reports suggested a possible role for such integration-targeted cellular genes (ITGs) in cervical carcinogenesis. Therefore, a comprehensive analysis of HPV integration events was undertaken using data collected from 14 publications, with 499 integration loci on human chromosomes included. It revealed that HPV DNA preferred to integrate into intragenic regions and gene-dense regions of human chromosomes. Intriguingly, the host cellular genes nearby the integration sites were found to be more transcriptionally active compared with control. Furthermore, analysis of the integration sites in the human genome revealed that there were several integration hotspots although all chromosomes were represented. The ITGs identified were found to be enriched in tumor-related terms and pathways using gene ontology and KEGG analysis. In line with this, three of six ITGs tested were found aberrantly expressed in cervical cancer tissues. Among them, it was demonstrated for the first time that MPPED2 could induce HeLa cell and SiHa cell G1/S transition block and cell proliferation retardation. Moreover, "knocking out" the integrated HPV fragment in HeLa cell line decreased expression of MYC located ∼500 kb downstream of the integration site, which provided the first experimental evidence supporting the hypothesis that integrated HPV fragment influence MYC expression via long distance chromatin interaction. Overall, the results of this comprehensive analysis implicated that dysregulation of ITGs caused by viral integration as possibly having an etiological involvement in cervical carcinogenesis. Show less
📄 PDF DOI: 10.1002/ijc.29872
MPPED2
J Li, L W Liu, L S Na +6 more · 2016 · Zhonghua xin xue guan bing za zhi · added 2026-04-24
To identify the potential mutations in a Chinese pedigree with hypertrophic cardiomyopathy (HCM), and to analyze the genotype-phenotype relationship in this pedigree. Clinical history and physical exa Show more
To identify the potential mutations in a Chinese pedigree with hypertrophic cardiomyopathy (HCM), and to analyze the genotype-phenotype relationship in this pedigree. Clinical history and physical examinations, electrocardiography (ECG), echocardiography (UCG), cardiac magnetic resonance (CMR) data were obtained from 10 members of a three-generation Chinese family with HCM. A total of 96 genes related to hereditary cardiomyopathy were detected by exon and boarding intron analyses in the proband using second-generation sequencing. Mutations identified in the proband were confirmed by bi-directional Sanger sequencing in the rest 9 family members and 300 healthy controls. Three mutations, including MYBPC3-P1208fs, ANK2-H556R and ANK2-P1974H, were identified in this pedigree. MYBPC3-P1208fs gene mutation was detected in 3 family members (proband, his mother and son), while this mutation was not detected in the rest family members. HCM was diagnosed in the proband and his mother by ECG, UCG and CMR. Son of the proband demonstrated early phenotype of HCM: although UCG and CMR were normal, ECG showed sinus bradycardia and paroxysmal supraventricular arrhythmias as well as ST segment changes. The onset age of HCM diagnosis of the proband and his mother was 42 and 50 years old, presented with palpitation and chest pain, and myocardial fibrosis sign in CMR. Furthermore, we found that left ventricular myocardial fibrosis is related to ECG changes (increasing r wave, ST segment change) in the proband and his mother. No HCM phenotype was evidenced in the 7 family members carrying ANK2-H556R and ANK2-P1974H mutations. Our results show that MYBPC3-P1208fs gene mutation is associated HCM phenotype in this Chinses pedigree. This mutation is associated with myocardial fibrosis and ST changes in HCM phenotype in this pedigree while ANK2-H556R and ANK2-P1974H mutations are not related to HCM phenotype in this family. Show less
no PDF DOI: 10.3760/cma.j.issn.0253-3758.2016.04.009
MYBPC3
Zhe Wang, A Dessa Sadovnick, Anthony L Traboulsee +12 more · 2016 · Neuron · Elsevier · added 2026-04-24
no PDF DOI: 10.1016/j.neuron.2016.09.028
NR1H3