👤 Can Liu

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3182
Articles
1983
Name variants
Also published as: A Liu, Ai Liu, Ai-Guo Liu, Aidong Liu, Aiguo Liu, Aihua Liu, Aijun Liu, Ailing Liu, Aimin Liu, Allen P Liu, Aman Liu, An Liu, An-Qi Liu, Ang-Jun Liu, Anjing Liu, Anjun Liu, Ankang Liu, Anling Liu, Anmin Liu, Annuo Liu, Anshu Liu, Ao Liu, Aoxing Liu, B Liu, Baihui Liu, Baixue Liu, Baiyan Liu, Ban Liu, Bang Liu, Bang-Quan Liu, Bao Liu, Bao-Cheng Liu, Baogang Liu, Baohui Liu, Baolan Liu, Baoli Liu, Baoning Liu, Baoxin Liu, Baoyi Liu, Bei Liu, Beibei Liu, Ben Liu, Bi-Cheng Liu, Bi-Feng Liu, Bihao Liu, Bilin Liu, Bin Liu, Bing Liu, Bing-Wen Liu, Bingcheng Liu, Bingjie Liu, Bingwen Liu, Bingxiao Liu, Bingya Liu, Bingyu Liu, Binjie Liu, Bo Liu, Bo-Gong Liu, Bo-Han Liu, Boao Liu, Bolin Liu, Boling Liu, Boqun Liu, Bowen Liu, Boxiang Liu, Boxin Liu, Boya Liu, Boyang Liu, Brian Y Liu, C Liu, C M Liu, C Q Liu, C-T Liu, C-Y Liu, Caihong Liu, Cailing Liu, Caiyan Liu, Can-Zhao Liu, Catherine H Liu, Chan Liu, Chang Liu, Chang-Bin Liu, Chang-Hai Liu, Chang-Ming Liu, Chang-Pan Liu, Chang-Peng Liu, Changbin Liu, Changjiang Liu, Changliang Liu, Changming Liu, Changqing Liu, Changtie Liu, Changya Liu, Changyun Liu, Chao Liu, Chao-Ming Liu, Chaohong Liu, Chaoqi Liu, Chaoyi Liu, Chelsea Liu, Chen Liu, Chenchen Liu, Chendong Liu, Cheng Liu, Cheng-Li Liu, Cheng-Wu Liu, Cheng-Yong Liu, Cheng-Yun Liu, Chengbo Liu, Chenge Liu, Chengguo Liu, Chenghui Liu, Chengkun Liu, Chenglong Liu, Chengxiang Liu, Chengyao Liu, Chengyun Liu, Chenmiao Liu, Chenming Liu, Chenshu Liu, Chenxing Liu, Chenxu Liu, Chenxuan Liu, Chi Liu, Chia-Chen Liu, Chia-Hung Liu, Chia-Jen Liu, Chia-Yang Liu, Chia-Yu Liu, Chiang Liu, Chin-Chih Liu, Chin-Ching Liu, Chin-San Liu, Ching-Hsuan Liu, Ching-Ti Liu, Chong Liu, Christine S Liu, ChuHao Liu, Chuan Liu, Chuanfeng Liu, Chuanxin Liu, Chuanyang Liu, Chun Liu, Chun-Chi Liu, Chun-Feng Liu, Chun-Lei Liu, Chun-Ming Liu, Chun-Xiao Liu, Chun-Yu Liu, Chunchi Liu, Chundong Liu, Chunfeng Liu, Chung-Cheng Liu, Chung-Ji Liu, Chunhua Liu, Chunlei Liu, Chunliang Liu, Chunling Liu, Chunming Liu, Chunpeng Liu, Chunping Liu, Chunsheng Liu, Chunwei Liu, Chunxiao Liu, Chunyan Liu, Chunying Liu, Chunyu Liu, Cici Liu, Clarissa M Liu, Cong Cong Liu, Cong Liu, Congcong Liu, Cui Liu, Cui-Cui Liu, Cuicui Liu, Cuijie Liu, Cuilan Liu, Cun Liu, Cun-Fei Liu, D Liu, Da Liu, Da-Ren Liu, Daiyun Liu, Dajiang J Liu, Dan Liu, Dan-Ning Liu, Dandan Liu, Danhui Liu, Danping Liu, Dantong Liu, Danyang Liu, Danyong Liu, Daoshen Liu, David Liu, David R Liu, Dawei Liu, Daxu Liu, Dayong Liu, Dazhi Liu, De-Pei Liu, De-Shun Liu, Dechao Liu, Dehui Liu, Deliang Liu, Deng-Xiang Liu, Depei Liu, Deping Liu, Derek Liu, Deruo Liu, Desheng Liu, Dewu Liu, Dexi Liu, Deyao Liu, Deying Liu, Dezhen Liu, Di Liu, Didi Liu, Ding-Ming Liu, Dingding Liu, Dinglu Liu, Dingxiang Liu, Dong Liu, Dong-Yun Liu, Dongang Liu, Dongbo Liu, Dongfang Liu, Donghui Liu, Dongjuan Liu, Dongliang Liu, Dongmei Liu, Dongming Liu, Dongping Liu, Dongxian Liu, Dongxue Liu, Dongyan Liu, Dongyang Liu, Dongyao Liu, Dongzhou Liu, Dudu Liu, Dunjiang Liu, Edison Tak-Bun Liu, En-Qi Liu, Enbin Liu, Enlong Liu, Enqi Liu, Erdong Liu, Erfeng Liu, Erxiong Liu, F Liu, F Z Liu, Fan Liu, Fan-Jie Liu, Fang Liu, Fang-Zhou Liu, Fangli Liu, Fangmei Liu, Fangping Liu, Fangqi Liu, Fangzhou Liu, Fani Liu, Fayu Liu, Fei Liu, Feifan Liu, Feilong Liu, Feiyan Liu, Feiyang Liu, Feiye Liu, Fen Liu, Fendou Liu, Feng Liu, Feng-Ying Liu, Fengbin Liu, Fengchao Liu, Fengen Liu, Fengguo Liu, Fengjiao Liu, Fengjie Liu, Fengjuan Liu, Fengqiong Liu, Fengsong Liu, Fonda Liu, Foqiu Liu, Fu-Jun Liu, Fu-Tong Liu, Fubao Liu, Fuhao Liu, Fuhong Liu, Fujun Liu, Gan Liu, Gang Liu, Gangli Liu, Ganqiang Liu, Gaohua Liu, Ge Liu, Ge-Li Liu, Gen Sheng Liu, Geng Liu, Geng-Hao Liu, Geoffrey Liu, George E Liu, George Liu, Geroge Liu, Gexiu Liu, Gongguan Liu, Guang Liu, Guangbin Liu, Guangfan Liu, Guanghao Liu, Guangliang Liu, Guangqin Liu, Guangwei Liu, Guangxu Liu, Guannan Liu, Guantong Liu, Gui Yao Liu, Gui-Fen Liu, Gui-Jing Liu, Gui-Rong Liu, Guibo Liu, Guidong Liu, Guihong Liu, Guiju Liu, Guili Liu, Guiqiong Liu, Guiquan Liu, Guisheng Liu, Guiyou Liu, Guiyuan Liu, Guning Liu, Guo-Liang Liu, Guochang Liu, Guodong Liu, Guohao Liu, Guojun Liu, Guoke Liu, Guoliang Liu, Guopin Liu, Guoqiang Liu, Guoqing Liu, Guoquan Liu, Guowen Liu, Guoyong Liu, H Liu, Hai Feng Liu, Hai-Jing Liu, Hai-Xia Liu, Hai-Yan Liu, Haibin Liu, Haichao Liu, Haifei Liu, Haifeng Liu, Hailan Liu, Hailin Liu, Hailing Liu, Haitao Liu, Haiyan Liu, Haiyang Liu, Haiying Liu, Haizhao Liu, Han Liu, Han-Fu Liu, Han-Qi Liu, Hancong Liu, Hang Liu, Hanhan Liu, Hanjiao Liu, Hanjie Liu, Hanmin Liu, Hanqing Liu, Hanxiang Liu, Hanyuan Liu, Hao Liu, Haobin Liu, Haodong Liu, Haogang Liu, Haojie Liu, Haokun Liu, Haoling Liu, Haowei Liu, Haowen Liu, Haoyue Liu, He-Kun Liu, Hehe Liu, Hekun Liu, Heliang Liu, Heng Liu, Hengan Liu, Hengru Liu, Hengtong Liu, Heyi Liu, Hong Juan Liu, Hong Liu, Hong Wei Liu, Hong-Bin Liu, Hong-Li Liu, Hong-Liang Liu, Hong-Tao Liu, Hong-Xiang Liu, Hong-Ying Liu, Hongbin Liu, Hongbing Liu, Hongfa Liu, Honghan Liu, Honghe Liu, Hongjian Liu, Hongjie Liu, Hongjun Liu, Hongli Liu, Hongliang Liu, Hongmei Liu, Hongqun Liu, Hongtao Liu, Hongwei Liu, Hongxiang Liu, Hongxing Liu, Hongyan Liu, Hongyang Liu, Hongyao Liu, Hongyu Liu, Hongyuan Liu, Houbao Liu, Hsiao-Ching Liu, Hsiao-Sheng Liu, Hsiaowei Liu, Hsu-Hsiang Liu, Hu Liu, Hua Liu, Hua-Cheng Liu, Hua-Ge Liu, Huadong Liu, Huaizheng Liu, Huan Liu, Huan-Yu Liu, Huanhuan Liu, Huanliang Liu, Huanyi Liu, Huatao Liu, Huawei Liu, Huayang Liu, Huazhen Liu, Hui Liu, Hui-Chao Liu, Hui-Fang Liu, Hui-Guo Liu, Hui-Hui Liu, Hui-Xin Liu, Hui-Ying Liu, Huibin Liu, Huidi Liu, Huihua Liu, Huihui Liu, Huijuan Liu, Huijun Liu, Huikun Liu, Huiling Liu, Huimao Liu, Huimin Liu, Huiming Liu, Huina Liu, Huiping Liu, Huiqing Liu, Huisheng Liu, Huiying Liu, Huiyu Liu, Hulin Liu, J Liu, J R Liu, J W Liu, J X Liu, J Z Liu, James K C Liu, Jamie Liu, Jay Liu, Ji Liu, Ji-Kai Liu, Ji-Long Liu, Ji-Xing Liu, Ji-Xuan Liu, Ji-Yun Liu, Jia Liu, Jia-Cheng Liu, Jia-Jun Liu, Jia-Qian Liu, Jia-Yao Liu, JiaXi Liu, Jiabin Liu, Jiachen Liu, Jiahao Liu, Jiahua Liu, Jiahui Liu, Jiajie Liu, Jiajuan Liu, Jiakun Liu, Jiali Liu, Jialin Liu, Jiamin Liu, Jiaming Liu, Jian Liu, Jian-Jun Liu, Jian-Kun Liu, Jian-hong Liu, Jian-shu Liu, Jianan Liu, Jianbin Liu, Jianbo Liu, Jiandong Liu, Jianfang Liu, Jianfeng Liu, Jiang Liu, Jiangang Liu, Jiangbin Liu, Jianghong Liu, Jianghua Liu, Jiangjiang Liu, Jiangjin Liu, Jiangling Liu, Jiangxin Liu, Jiangyan Liu, Jianhua Liu, Jianhui Liu, Jiani Liu, Jianing Liu, Jianjiang Liu, Jianjun Liu, Jiankang Liu, Jiankun Liu, Jianlei Liu, Jianmei Liu, Jianmin Liu, Jiannan Liu, Jianping Liu, Jiantao Liu, Jianwei Liu, Jianxi Liu, Jianxin Liu, Jianyong Liu, Jianyu Liu, Jianyun Liu, Jiao Liu, Jiaojiao Liu, Jiaoyang Liu, Jiaqi Liu, Jiaqing Liu, Jiawen Liu, Jiaxian Liu, Jiaxiang Liu, Jiaxin Liu, Jiayan Liu, Jiayi Liu, Jiayin Liu, Jiaying Liu, Jiayu Liu, Jiayun Liu, Jiazhe Liu, Jiazheng Liu, Jiazhuo Liu, Jidan Liu, Jie Liu, Jie-Qing Liu, Jierong Liu, Jiewei Liu, Jiewen Liu, Jieying Liu, Jieyu Liu, Jihe Liu, Jiheng Liu, Jin Liu, Jin-Juan Liu, Jin-Qing Liu, Jinbao Liu, Jinbo Liu, Jincheng Liu, Jindi Liu, Jinfeng Liu, Jing Liu, Jing Min Liu, Jing-Crystal Liu, Jing-Hua Liu, Jing-Ying Liu, Jing-Yu Liu, Jingbo Liu, Jingchong Liu, Jingfang Liu, Jingfeng Liu, Jingfu Liu, Jinghui Liu, Jingjie Liu, Jingjing Liu, Jingmeng Liu, Jingmin Liu, Jingqi Liu, Jingquan Liu, Jingqun Liu, Jingsheng Liu, Jingwei Liu, Jingwen Liu, Jingxing Liu, Jingyi Liu, Jingying Liu, Jingyun Liu, Jingzhong Liu, Jinjie Liu, Jinlian Liu, Jinlong Liu, Jinman Liu, Jinpei Liu, Jinpeng Liu, Jinping Liu, Jinqin Liu, Jinrong Liu, Jinsheng Liu, Jinsong Liu, Jinsuo Liu, Jinxiang Liu, Jinxin Liu, Jinxing Liu, Jinyue Liu, Jinze Liu, Jinzhao Liu, Jinzhi Liu, Jiong Liu, Jishan Liu, Jitao Liu, Jiwei Liu, Jixin Liu, Jonathan Liu, Joyce F Liu, Joyce Liu, Ju Liu, Ju-Fang Liu, Juan Liu, Juanjuan Liu, Juanxi Liu, Jue Liu, Jui-Tung Liu, Jun Liu, Jun O Liu, Jun Ting Liu, Jun Yi Liu, Jun-Jen Liu, Jun-Yan Liu, Jun-Yi Liu, Junbao Liu, Junchao Liu, Junfen Liu, Junhui Liu, Junjiang Liu, Junjie Liu, Junjin Liu, Junjun Liu, Junlin Liu, Junling Liu, Junnian Liu, Junpeng Liu, Junqi Liu, Junrong Liu, Juntao Liu, Juntian Liu, Junwen Liu, Junwu Liu, Junxi Liu, Junyan Liu, Junye Liu, Junying Liu, Junyu Liu, Juyao Liu, Kai Liu, Kai-Zheng Liu, Kaidong Liu, Kaijing Liu, Kaikun Liu, Kaiqi Liu, Kaisheng Liu, Kaitai Liu, Kaiwen Liu, Kang Liu, Kang-le Liu, Kangdong Liu, Kangwei Liu, Kathleen D Liu, Ke Liu, Ke-Tong Liu, Kechun Liu, Kehui Liu, Kejia Liu, Keng-Hau Liu, Keqiang Liu, Kexin Liu, Kiang Liu, Kuangyi Liu, Kun Liu, Kun-Cheng Liu, Kwei-Yan Liu, L L Liu, L Liu, L W Liu, Lan Liu, Lan-Xiang Liu, Lang Liu, Lanhao Liu, Le Liu, Lebin Liu, Lei Liu, Lele Liu, Leping Liu, Li Liu, Li-Fang Liu, Li-Min Liu, Li-Rong Liu, Li-Wen Liu, Li-Xuan Liu, Li-Ying Liu, Li-ping Liu, Lian Liu, Lianfei Liu, Liang Liu, Liang-Chen Liu, Liang-Feng Liu, Liangguo Liu, Liangji Liu, Liangjia Liu, Liangliang Liu, Liangyu Liu, Lianxin Liu, Lianyong Liu, Libin Liu, Lichao Liu, Lichun Liu, Lidong Liu, Liegang Liu, Lifang Liu, Ligang Liu, Lihua Liu, Lijuan Liu, Lijun Liu, Lili Liu, Liling Liu, Limin Liu, Liming Liu, Lin Liu, Lina Liu, Ling Liu, Ling-Yun Liu, Ling-Zhi Liu, Lingfei Liu, Lingjiao Liu, Lingjuan Liu, Linglong Liu, Lingyan Liu, Lining Liu, Linlin Liu, Linqing Liu, Linwen Liu, Liping Liu, Liqing Liu, Liqiong Liu, Liqun Liu, Lirong Liu, Liru Liu, Liu Liu, Liumei Liu, Liusheng Liu, Liwen Liu, Lixia Liu, Lixian Liu, Lixiao Liu, Liying Liu, Liyue Liu, Lizhen Liu, Long Liu, Longfei Liu, Longjian Liu, Longqian Liu, Longyang Liu, Longzhou Liu, Lu Liu, Luhong Liu, Lulu Liu, Luming Liu, Lunxu Liu, Luping Liu, Lushan Liu, Lv Liu, M L Liu, M Liu, Man Liu, Man-Ru Liu, Manjiao Liu, Manqi Liu, Manran Liu, Maolin Liu, Mei Liu, Mei-mei Liu, Meicen Liu, Meifang Liu, Meijiao Liu, Meijing Liu, Meijuan Liu, Meijun Liu, Meiling Liu, Meimei Liu, Meixin Liu, Meiyan Liu, Meng Han Liu, Meng Liu, Meng-Hui Liu, Meng-Meng Liu, Meng-Yue Liu, Mengduan Liu, Mengfan Liu, Mengfei Liu, Menggang Liu, Menghan Liu, Menghua Liu, Menghui Liu, Mengjia Liu, Mengjiao Liu, Mengke Liu, Menglin Liu, Mengling Liu, Mengmei Liu, Mengqi Liu, Mengqian Liu, Mengxi Liu, Mengxue Liu, Mengyang Liu, Mengying Liu, Mengyu Liu, Mengyuan Liu, Mengzhen Liu, Mi Liu, Mi-Hua Liu, Mi-Min Liu, Miao Liu, Miaoliang Liu, Min Liu, Minda Liu, Minetta C Liu, Ming Liu, Ming-Jiang Liu, Ming-Qi Liu, Mingcheng Liu, Mingchun Liu, Mingfan Liu, Minghui Liu, Mingjiang Liu, Mingjing Liu, Mingjun Liu, Mingli Liu, Mingming Liu, Mingna Liu, Mingqin Liu, Mingrui Liu, Mingsen Liu, Mingsong Liu, Mingxiao Liu, Mingxing Liu, Mingxu Liu, Mingyang Liu, Mingyao Liu, Mingying Liu, Mingyu Liu, Minhao Liu, Minxia Liu, Mo-Nan Liu, Modan Liu, Mouze Liu, Muqiu Liu, Musang Liu, N A Liu, N Liu, Na Liu, Na-Nv Liu, Na-Wei Liu, Nai-feng Liu, Naihua Liu, Naili Liu, Nan Liu, Nan-Song Liu, Nana Liu, Nannan Liu, Nanxi Liu, Ni Liu, Nian Liu, Ning Liu, Ning'ang Liu, Ningning Liu, Niya Liu, Ou Liu, Ouxuan Liu, P C Liu, Pan Liu, Panhong Liu, Panting Liu, Paul Liu, Pei Liu, Pei-Ning Liu, Peijian Liu, Peijie Liu, Peijun Liu, Peilong Liu, Peiqi Liu, Peiqing Liu, Peiwei Liu, Peixi Liu, Peiyao Liu, Peizhong Liu, Peng Liu, Pengcheng Liu, Pengfei Liu, Penghong Liu, Pengli Liu, Pengtao Liu, Pengyu Liu, Pengyuan Liu, Pentao Liu, Peter S Liu, Piaopiao Liu, Pinduo Liu, Ping Liu, Ping-Yen Liu, Pinghuai Liu, Pingping Liu, Pingsheng Liu, Q Liu, Qi Liu, Qi-Xian Liu, Qian Liu, Qian-Wen Liu, Qiang Liu, Qiang-Yuan Liu, Qiangyun Liu, Qianjin Liu, Qianqi Liu, Qianshuo Liu, Qianwei Liu, Qiao-Hong Liu, Qiaofeng Liu, Qiaoyan Liu, Qiaozhen Liu, Qiji Liu, Qiming Liu, Qin Liu, Qinfang Liu, Qing Liu, Qing-Huai Liu, Qing-Rong Liu, Qingbin Liu, Qingbo Liu, Qingguang Liu, Qingguo Liu, Qinghao Liu, Qinghong Liu, Qinghua Liu, Qinghuai Liu, Qinghuan Liu, Qinglei Liu, Qingping Liu, Qingqing Liu, Qingquan Liu, Qingsong Liu, Qingxia Liu, Qingxiang Liu, Qingyang Liu, Qingyou Liu, Qingyun Liu, Qingzhuo Liu, Qinqin Liu, Qiong Liu, Qiu-Ping Liu, Qiulei Liu, Qiuli Liu, Qiulu Liu, Qiushi Liu, Qiuxu Liu, Qiuyu Liu, Qiuyue Liu, Qiwei Liu, Qiyao Liu, Qiye Liu, Qizhan Liu, Quan Liu, Quan-Jun Liu, Quanxin Liu, Quanying Liu, Quanzhong Liu, Quentin Liu, Qun Liu, Qunlong Liu, Qunpeng Liu, R F Liu, R Liu, R Y Liu, Ran Liu, Rangru Liu, Ranran Liu, Ren Liu, Renling Liu, Ri Liu, Rong Liu, Rong-Zong Liu, Rongfei Liu, Ronghua Liu, Rongxia Liu, Rongxun Liu, Rui Liu, Rui-Jie Liu, Rui-Tian Liu, Rui-Xuan Liu, Ruichen Liu, Ruihua Liu, Ruijie Liu, Ruijuan Liu, Ruilong Liu, Ruiping Liu, Ruiqi Liu, Ruitong Liu, Ruixia Liu, Ruiyi Liu, Ruizao Liu, Runjia Liu, Runjie Liu, Runni Liu, Runping Liu, Ruochen Liu, Ruotian Liu, Ruowen Liu, Ruoyang Liu, Ruyi Liu, Ruyue Liu, S Liu, Saiji Liu, Sasa Liu, Sen Liu, Senchen Liu, Senqi Liu, Sha Liu, Shan Liu, Shan-Shan Liu, Shandong Liu, Shang-Feng Liu, Shang-Xin Liu, Shangjing Liu, Shangxin Liu, Shangyu Liu, Shangyuan Liu, Shangyun Liu, Shanhui Liu, Shanling Liu, Shanshan Liu, Shao-Bin Liu, Shao-Jun Liu, Shao-Yuan Liu, Shaobo Liu, Shaocheng Liu, Shaohua Liu, Shaojun Liu, Shaoqing Liu, Shaowei Liu, Shaoying Liu, Shaoyou Liu, Shaoyu Liu, Shaozhen Liu, Shasha Liu, Sheng Liu, Shengbin Liu, Shengjun Liu, Shengnan Liu, Shengyang Liu, Shengzhi Liu, Shengzhuo Liu, Shenhai Liu, Shenping Liu, Shi Liu, Shi-Lian Liu, Shi-Wei Liu, Shi-Yong Liu, Shi-guo Liu, ShiWei Liu, Shih-Ping Liu, Shijia Liu, Shijian Liu, Shijie Liu, Shijun Liu, Shikai Liu, Shikun Liu, Shilin Liu, Shing-Hwa Liu, Shiping Liu, Shiqian Liu, Shiquan Liu, Shiru Liu, Shixi Liu, Shiyan Liu, Shiyang Liu, Shiying Liu, Shiyu Liu, Shiyuan Liu, Shou-Sheng Liu, Shouguo Liu, Shoupei Liu, Shouxin Liu, Shouyang Liu, Shu Liu, Shu-Chen Liu, Shu-Jing Liu, Shu-Lin Liu, Shu-Qiang Liu, Shu-Qin Liu, Shuai Liu, Shuaishuai Liu, Shuang Liu, Shuangli Liu, Shuangzhu Liu, Shuhong Liu, Shuhua Liu, Shui-Bing Liu, Shujie Liu, Shujing Liu, Shujun Liu, Shulin Liu, Shuling Liu, Shumin Liu, Shun-Mei Liu, Shunfang Liu, Shuning Liu, Shunming Liu, Shuqian Liu, Shuqing Liu, Shuwen Liu, Shuxi Liu, Shuxian Liu, Shuya Liu, Shuyan Liu, Shuyu Liu, Si-Jin Liu, Si-Xu Liu, Si-Yan Liu, Si-jun Liu, Sicheng Liu, Sidan Liu, Side Liu, Sihao Liu, Sijing Liu, Sijun Liu, Silvia Liu, Simin Liu, Sipu Liu, Siqi Liu, Siqin Liu, Siru Liu, Sirui Liu, Sisi Liu, Sitian Liu, Siwen Liu, Sixi Liu, Sixin Liu, Sixiu Liu, Sixu Liu, Siyao Liu, Siyi Liu, Siyu Liu, Siyuan Liu, Song Liu, Song-Fang Liu, Song-Mei Liu, Song-Ping Liu, Songfang Liu, Songhui Liu, Songqin Liu, Songsong Liu, Songyi Liu, Su Liu, Su-Yun Liu, Sudong Liu, Suhuan Liu, Sui-Feng Liu, Suling Liu, Suosi Liu, Sushuang Liu, Susu Liu, Szu-Heng Liu, T H Liu, T Liu, Ta-Chih Liu, Taihang Liu, Taixiang Liu, Tang Liu, Tao Liu, Taoli Liu, Taotao Liu, Te Liu, Teng Liu, Tengfei Liu, Tengli Liu, Teresa T Liu, Tian Liu, Tian Shu Liu, Tianhao Liu, Tianhu Liu, Tianjia Liu, Tianjiao Liu, Tianlai Liu, Tianlang Liu, Tianlong Liu, Tianqiang Liu, Tianrui Liu, Tianshu Liu, Tiantian Liu, Tianyao Liu, Tianyi Liu, Tianyu Liu, Tianze Liu, Tiemin Liu, Tina Liu, Ting Liu, Ting-Li Liu, Ting-Ting Liu, Ting-Yuan Liu, Tingjiao Liu, Tingting Liu, Tong Liu, Tonglin Liu, Tongtong Liu, Tongyan Liu, Tongyu Liu, Tongyun Liu, Tongzheng Liu, Tsang-Wu Liu, Tsung-Yun Liu, Vincent W S Liu, W Liu, W-Y Liu, Wan Liu, Wan-Chun Liu, Wan-Di Liu, Wan-Guo Liu, Wan-Ying Liu, Wang Liu, Wangrui Liu, Wanguo Liu, Wangyang Liu, Wanjun Liu, Wanli Liu, Wanlu Liu, Wanqi Liu, Wanqing Liu, Wanting Liu, Wei Liu, Wei-Chieh Liu, Wei-Hsuan Liu, Wei-Hua Liu, Weida Liu, Weifang Liu, Weifeng Liu, Weiguo Liu, Weihai Liu, Weihong Liu, Weijian Liu, Weijie Liu, Weijun Liu, Weilin Liu, Weimin Liu, Weiming Liu, Weina Liu, Weiqin Liu, Weiqing Liu, Weiren Liu, Weisheng Liu, Weishuo Liu, Weiwei Liu, Weiyang Liu, Wen Liu, Wen Yuan Liu, Wen-Chun Liu, Wen-Di Liu, Wen-Fang Liu, Wen-Jie Liu, Wen-Jing Liu, Wen-Qiang Liu, Wen-Tao Liu, Wen-ling Liu, Wenbang Liu, Wenbin Liu, Wenbo Liu, Wenchao Liu, Wenen Liu, Wenfeng Liu, Wenhan Liu, Wenhao Liu, Wenhua Liu, Wenjie Liu, Wenjing Liu, Wenlang Liu, Wenli Liu, Wenling Liu, Wenlong Liu, Wenna Liu, Wenping Liu, Wenqi Liu, Wenrui Liu, Wensheng Liu, Wentao Liu, Wenwu Liu, Wenxiang Liu, Wenxuan Liu, Wenya Liu, Wenyan Liu, Wenyi Liu, Wenzhong Liu, Wu Liu, Wuping Liu, Wuyang Liu, X C Liu, X Liu, X P Liu, X-D Liu, Xi Liu, Xi-Yu Liu, Xia Liu, Xia-Meng Liu, Xialin Liu, Xian Liu, Xianbao Liu, Xianchen Liu, Xianda Liu, Xiang Liu, Xiang-Qian Liu, Xiang-Yu Liu, Xiangchen Liu, Xiangfei Liu, Xianglan Liu, Xiangli Liu, Xiangliang Liu, Xianglu Liu, Xiangning Liu, Xiangping Liu, Xiangsheng Liu, Xiangtao Liu, Xiangting Liu, Xiangxiang Liu, Xiangxuan Liu, Xiangyong Liu, Xiangyu Liu, Xiangyun Liu, Xianli Liu, Xianling Liu, Xiansheng Liu, Xianyang Liu, Xiao Dong Liu, Xiao Liu, Xiao Yan Liu, Xiao-Cheng Liu, Xiao-Dan Liu, Xiao-Gang Liu, Xiao-Guang Liu, Xiao-Huan Liu, Xiao-Jiao Liu, Xiao-Li Liu, Xiao-Ling Liu, Xiao-Ning Liu, Xiao-Qiu Liu, Xiao-Qun Liu, Xiao-Rong Liu, Xiao-Song Liu, Xiao-Xiao Liu, Xiao-lan Liu, Xiaoan Liu, Xiaobai Liu, Xiaobei Liu, Xiaobing Liu, Xiaocen Liu, Xiaochuan Liu, Xiaocong Liu, Xiaodan Liu, Xiaoding Liu, Xiaodong Liu, Xiaofan Liu, Xiaofang Liu, Xiaofei Liu, Xiaogang Liu, Xiaoguang Liu, Xiaoguang Margaret Liu, Xiaohan Liu, Xiaoheng Liu, Xiaohong Liu, Xiaohua Liu, Xiaohuan Liu, Xiaohui Liu, Xiaojie Liu, Xiaojing Liu, Xiaoju Liu, Xiaojun Liu, Xiaole Shirley Liu, Xiaolei Liu, Xiaoli Liu, Xiaolin Liu, Xiaoling Liu, Xiaoman Liu, Xiaomei Liu, Xiaomeng Liu, Xiaomin Liu, Xiaoming Liu, Xiaona Liu, Xiaonan Liu, Xiaopeng Liu, Xiaoping Liu, Xiaoqian Liu, Xiaoqiang Liu, Xiaoqin Liu, Xiaoqing Liu, Xiaoran Liu, Xiaosong Liu, Xiaotian Liu, Xiaoting Liu, Xiaowei Liu, Xiaoxi Liu, Xiaoxia Liu, Xiaoxiao Liu, Xiaoxu Liu, Xiaoxue Liu, Xiaoya Liu, Xiaoyan Liu, Xiaoyang Liu, Xiaoye Liu, Xiaoying Liu, Xiaoyong Liu, Xiaoyu Liu, Xiawen Liu, Xibao Liu, Xibing Liu, Xie-hong Liu, Xiehe Liu, Xiguang Liu, Xijun Liu, Xili Liu, Xin Liu, Xin-Hua Liu, Xin-Yan Liu, Xinbo Liu, Xinchang Liu, Xing Liu, Xing-De Liu, Xing-Li Liu, Xing-Yang Liu, Xingbang Liu, Xingde Liu, Xinghua Liu, Xinghui Liu, Xingjing Liu, Xinglei Liu, Xingli Liu, Xinglong Liu, Xinguo Liu, Xingxiang Liu, Xingyi Liu, Xingyu Liu, Xinhua Liu, Xinjun Liu, Xinlei Liu, Xinli Liu, Xinmei Liu, Xinmin Liu, Xinran Liu, Xinru Liu, Xinrui Liu, Xintong Liu, Xinxin Liu, Xinyao Liu, Xinyi Liu, Xinying Liu, Xinyong Liu, Xinyu Liu, Xinyue Liu, Xiong Liu, Xiqiang Liu, Xiru Liu, Xishan Liu, Xiu Liu, Xiufen Liu, Xiufeng Liu, Xiuheng Liu, Xiuling Liu, Xiumei Liu, Xiuqin Liu, Xiyong Liu, Xu Liu, Xu-Dong Liu, Xu-Hui Liu, Xuan Liu, Xuanlin Liu, Xuanyu Liu, Xuanzhu Liu, Xue Liu, Xue-Lian Liu, Xue-Min Liu, Xue-Qing Liu, Xue-Zheng Liu, Xuefang Liu, Xuejing Liu, Xuekui Liu, Xuelan Liu, Xueling Liu, Xuemei Liu, Xuemeng Liu, Xuemin Liu, Xueping Liu, Xueqin Liu, Xueqing Liu, Xueru Liu, Xuesen Liu, Xueshibojie Liu, Xuesong Liu, Xueting Liu, Xuewei Liu, Xuewen Liu, Xuexiu Liu, Xueying Liu, Xueyuan Liu, Xuezhen Liu, Xuezheng Liu, Xuezhi Liu, Xufeng Liu, Xuguang Liu, Xujie Liu, Xulin Liu, Xuming Liu, Xunhua Liu, Xunyue Liu, Xuxia Liu, Xuxu Liu, Xuyi Liu, Xuying Liu, Y H Liu, Y L Liu, Y Liu, Y Y Liu, Ya Liu, Ya-Jin Liu, Ya-Kun Liu, Ya-Wei Liu, Yadong Liu, Yafei Liu, Yajing Liu, Yajuan Liu, Yaling Liu, Yalu Liu, Yan Liu, Yan-Li Liu, Yanan Liu, Yanchao Liu, Yanchen Liu, Yandong Liu, Yanfei Liu, Yanfen Liu, Yanfeng Liu, Yang Liu, Yange Liu, Yangfan Liu, Yangfan P Liu, Yangjun Liu, Yangkai Liu, Yangruiyu Liu, Yangyang Liu, Yanhong Liu, Yanhua Liu, Yanhui Liu, Yanjie Liu, Yanju Liu, Yanjun Liu, Yankuo Liu, Yanli Liu, Yanliang Liu, Yanling Liu, Yanman Liu, Yanmin Liu, Yanping Liu, Yanqing Liu, Yanqiu Liu, Yanquan Liu, Yanru Liu, Yansheng Liu, Yansong Liu, Yanting Liu, Yanwu Liu, Yanxiao Liu, Yanyan Liu, Yanyao Liu, Yanying Liu, Yanyun Liu, Yao Liu, Yao-Hui Liu, Yaobo Liu, Yaoquan Liu, Yaou Liu, Yaowen Liu, Yaoyao Liu, Yaozhong Liu, Yaping Liu, Yaqiong Liu, Yarong Liu, Yaru Liu, Yating Liu, Yaxin Liu, Ye Liu, Ye-Dan Liu, Yehai Liu, Yen-Chen Liu, Yen-Chun Liu, Yen-Nien Liu, Yeqing Liu, Yi Liu, Yi-Chang Liu, Yi-Chien Liu, Yi-Han Liu, Yi-Hung Liu, Yi-Jia Liu, Yi-Ling Liu, Yi-Meng Liu, Yi-Ming Liu, Yi-Yun Liu, Yi-Zhang Liu, YiRan Liu, Yibin Liu, Yibing Liu, Yicun Liu, Yidan Liu, Yidong Liu, Yifan Liu, Yifu Liu, Yihao Liu, Yiheng Liu, Yihui Liu, Yijing Liu, Yilei Liu, Yili Liu, Yilin Liu, Yimei Liu, Yiming Liu, Yin Liu, Yin-Ping Liu, Yinchu Liu, Yinfang Liu, Ying Liu, Ying Poi Liu, Yingchun Liu, Yinghua Liu, Yinghuan Liu, Yinghui Liu, Yingjun Liu, Yingli Liu, Yingwei Liu, Yingxia Liu, Yingyan Liu, Yingyi Liu, Yingying Liu, Yingzi Liu, Yinhe Liu, Yinhui Liu, Yining Liu, Yinjiang Liu, Yinping Liu, Yinuo Liu, Yiping Liu, Yiqing Liu, Yitian Liu, Yiting Liu, Yitong Liu, Yiwei Liu, Yiwen Liu, Yixiang Liu, Yixiao Liu, Yixuan Liu, Yiyang Liu, Yiyi Liu, Yiyuan Liu, Yiyun Liu, Yizhi Liu, Yizhuo Liu, Yong Liu, Yong Mei Liu, Yong-Chao Liu, Yong-Hong Liu, Yong-Jian Liu, Yong-Jun Liu, Yong-Tai Liu, Yong-da Liu, Yongchao Liu, Yonggang Liu, Yonggao Liu, Yonghong Liu, Yonghua Liu, Yongjian Liu, Yongjie Liu, Yongjun Liu, Yongli Liu, Yongmei Liu, Yongming Liu, Yongqiang Liu, Yongshuo Liu, Yongtai Liu, Yongtao Liu, Yongtong Liu, Yongxiao Liu, Yongyue Liu, You Liu, You-ping Liu, Youan Liu, Youbin Liu, Youdong Liu, Youhan Liu, Youlian Liu, Youwen Liu, Yu Liu, Yu Xuan Liu, Yu-Chen Liu, Yu-Ching Liu, Yu-Hui Liu, Yu-Li Liu, Yu-Lin Liu, Yu-Peng Liu, Yu-Wei Liu, Yu-Zhang Liu, YuHeng Liu, Yuan Liu, Yuan-Bo Liu, Yuan-Jie Liu, Yuan-Tao Liu, YuanHua Liu, Yuanchu Liu, Yuanfa Liu, Yuanhang Liu, Yuanhui Liu, Yuanjia Liu, Yuanjiao Liu, Yuanjun Liu, Yuanliang Liu, Yuantao Liu, Yuantong Liu, Yuanxiang Liu, Yuanxin Liu, Yuanxing Liu, Yuanying Liu, Yuanyuan Liu, Yubin Liu, Yuchen Liu, Yue Liu, Yuecheng Liu, Yuefang Liu, Yuehong Liu, Yueli Liu, Yueping Liu, Yuetong Liu, Yuexi Liu, Yuexin Liu, Yuexing Liu, Yueyang Liu, Yueyun Liu, Yufan Liu, Yufei Liu, Yufeng Liu, Yuhao Liu, Yuhe Liu, Yujia Liu, Yujiang Liu, Yujie Liu, Yujun Liu, Yulan Liu, Yuling Liu, Yulong Liu, Yumei Liu, Yumiao Liu, Yun Liu, Yun-Cai Liu, Yun-Qiang Liu, Yun-Ru Liu, Yun-Zi Liu, Yunfen Liu, Yunfeng Liu, Yuning Liu, Yunjie Liu, Yunlong Liu, Yunqi Liu, Yunqiang Liu, Yuntao Liu, Yunuan Liu, Yunuo Liu, Yunxia Liu, Yunyun Liu, Yuping Liu, Yupu Liu, Yuqi Liu, Yuqiang Liu, Yuqing Liu, Yurong Liu, Yuru Liu, Yusen Liu, Yutao Liu, Yutian Liu, Yuting Liu, Yutong Liu, Yuwei Liu, Yuxi Liu, Yuxia Liu, Yuxiang Liu, Yuxin Liu, Yuxuan Liu, Yuyan Liu, Yuyi Liu, Yuyu Liu, Yuyuan Liu, Yuzhen Liu, Yv-Xuan Liu, Z H Liu, Z Q Liu, Z Z Liu, Zaiqiang Liu, Zan Liu, Zaoqu Liu, Ze Liu, Zefeng Liu, Zekun Liu, Zeming Liu, Zengfu Liu, Zeyu Liu, Zezhou Liu, Zhangyu Liu, Zhangyuan Liu, Zhansheng Liu, Zhao Liu, Zhaoguo Liu, Zhaoli Liu, Zhaorui Liu, Zhaotian Liu, Zhaoxiang Liu, Zhaoxun Liu, Zhaoyang Liu, Zhe Liu, Zhekai Liu, Zheliang Liu, Zhen Liu, Zhen-Lin Liu, Zhendong Liu, Zhenfang Liu, Zhenfeng Liu, Zheng Liu, Zheng-Hong Liu, Zheng-Yu Liu, ZhengYi Liu, Zhengbing Liu, Zhengchuang Liu, Zhengdong Liu, Zhenghao Liu, Zhengkun Liu, Zhengtang Liu, Zhengting Liu, Zhenguo Liu, Zhengxia Liu, Zhengye Liu, Zhenhai Liu, Zhenhao Liu, Zhenhua Liu, Zhenjiang Liu, Zhenjiao Liu, Zhenjie Liu, Zhenkui Liu, Zhenlei Liu, Zhenmi Liu, Zhenming Liu, Zhenna Liu, Zhenqian Liu, Zhenqiu Liu, Zhenwei Liu, Zhenxing Liu, Zhenxiu Liu, Zhenzhen Liu, Zhenzhu Liu, Zhi Liu, Zhi Y Liu, Zhi-Fen Liu, Zhi-Guo Liu, Zhi-Jie Liu, Zhi-Kai Liu, Zhi-Ping Liu, Zhi-Ren Liu, Zhi-Wen Liu, Zhi-Ying Liu, Zhicheng Liu, Zhifang Liu, Zhigang Liu, Zhiguo Liu, Zhihan Liu, Zhihao Liu, Zhihong Liu, Zhihua Liu, Zhihui Liu, Zhijia Liu, Zhijie Liu, Zhikui Liu, Zhili Liu, Zhiming Liu, Zhipeng Liu, Zhiping Liu, Zhiqian Liu, Zhiqiang Liu, Zhiru Liu, Zhirui Liu, Zhishuo Liu, Zhitao Liu, Zhiteng Liu, Zhiwei Liu, Zhixiang Liu, Zhixue Liu, Zhiyan Liu, Zhiying Liu, Zhiyong Liu, Zhiyuan Liu, Zhong Liu, Zhong Wu Liu, Zhong-Hua Liu, Zhong-Min Liu, Zhong-Qiu Liu, Zhong-Wu Liu, Zhong-Ying Liu, Zhongchun Liu, Zhongguo Liu, Zhonghua Liu, Zhongjian Liu, Zhongjuan Liu, Zhongmin Liu, Zhongqi Liu, Zhongqiu Liu, Zhongwei Liu, Zhongyu Liu, Zhongyue Liu, Zhongzhong Liu, Zhou Liu, Zhou-di Liu, Zhu Liu, Zhuangjun Liu, Zhuanhua Liu, Zhuo Liu, Zhuoyuan Liu, Zi Hao Liu, Zi-Hao Liu, Zi-Lun Liu, Zi-Ye Liu, Zi-wen Liu, Zichuan Liu, Zihang Liu, Zihao Liu, Zihe Liu, Ziheng Liu, Zijia Liu, Zijian Liu, Zijing J Liu, Zimeng Liu, Ziqian Liu, Ziqin Liu, Ziteng Liu, Zitian Liu, Ziwei Liu, Zixi Liu, Zixuan Liu, Ziyang Liu, Ziying Liu, Ziyou Liu, Ziyuan Liu, Ziyue Liu, Zong-Chao Liu, Zong-Yuan Liu, Zonghua Liu, Zongjun Liu, Zongtao Liu, Zongxiang Liu, Zu-Guo Liu, Zuguo Liu, Zuohua Liu, Zuojin Liu, Zuolu Liu, Zuyi Liu, Zuyun Liu
articles

Demyelination contributes to depression comorbidity in a rat model of chronic epilepsy via dysregulation of Olig2/LINGO-1 and disturbance of calcium homeostasis.

Teng Ma, Baichuan Li, Yifan Le +7 more · 2019 · Experimental neurology · Elsevier · added 2026-04-24
Depression is the most common comorbidity among patients with epilepsy. Despite prior assumptions that antiepileptic drugs are to blame, more and more pathological studies have shown that latent neuro Show more
Depression is the most common comorbidity among patients with epilepsy. Despite prior assumptions that antiepileptic drugs are to blame, more and more pathological studies have shown that latent neurological alterations associated with white matter injury and demyelination may underlie this link. However, whether disturbances in cerebral myelination contribute to the initiation of depression in epilepsy remains unclear. In the present study, we investigated the connection between demyelination disorders and the development of depression comorbidity in epilepsy. We first induced spontaneous recurrent epilepticus seizure (SRS) in young rats with pilocarpine. We then established depressive behaviors by recurrent forced swimming test and evaluate the depression state by sucrose preference test. The ratio of depression comorbidity in SRS rats was then calculated. Next, myelination in SRS-Depressed (SRS-D) rats was explored via PCR, western blotting, and immunohistochemistry for the key myelin promotion factor, Olig2 and inhibition factor, LINGO-1. Finally, in situ RNA hybridization of NCX3, one of the dominant Ca Show less
no PDF DOI: 10.1016/j.expneurol.2019.113034
LINGO1

Whole exome and target sequencing identifies MAP2K5 as novel susceptibility gene for familial non-medullary thyroid carcinoma.

Feng Ye, Hongwei Gao, Lin Xiao +19 more · 2019 · International journal of cancer · Wiley · added 2026-04-24
Although the genotype-phenotype for familial medullary thyroid carcinoma (FMTC) is well studied, only few low susceptibility risk loci were identified for familial non-medullary thyroid carcinoma (FNM Show more
Although the genotype-phenotype for familial medullary thyroid carcinoma (FMTC) is well studied, only few low susceptibility risk loci were identified for familial non-medullary thyroid carcinoma (FNMTC). The aim of this study is to screen and identify high-penetrate genes for FNMTC. A total of 34 families with more than two first-degree relatives diagnosed as papillary thyroid cancer without other familial syndrome were recruited. Whole exome and target gene sequencing were performed for candidate variants. These variants were screened and analyzed with ESP6500, ExAC, 1000 genomes project, and the Cancer Genome Atlas (TCGA) with SIFT score and Polyphen2 prediction. Finally, we identified recurrent genetic mutation of MAP2K5 variants c.G961A and c.T1100C (p. A321T and p.M367 T) as susceptibility loci for FNMTC. The frequencies of MAP2K5 c.G961A and c.T1100C were found, 0.0385 and 0.0259 in FNMTC and 0 and 0.00022523 in healthy Chinese controls (n = 2200, P < 0.001), respectively. Both variants were located in the protein kinase domain. The functional study showed that MAP2K5 A321T or M367 T could consistently phosphorylate downstream protein ERK5 on site Ser731 + Thr733 or Ser496, promoting nuclear translocation and subsequently altering target gene expressions. Our data revealed that MAP2K5 variants A321T or M367 T can activate MAP2K5-ERK5 pathway, alter downstream gene expression, and subsequently induce thyroid epithelial cell malignant transformation. While classic MAP2K1/2(MEK1/2)-ERK1/2 signaling is well known for driving sporadic NMTC, our research indicated that MAP2K5 (MEK5) is a susceptibility gene for FNMTC. These findings highlight the potential application of MAP2K5 for molecular diagnosis as well as early prevention. Show less
no PDF DOI: 10.1002/ijc.31825
MAP2K5

Disentangling the genetics of lean mass.

David Karasik, M Carola Zillikens, Yi-Hsiang Hsu +154 more · 2019 · The American journal of clinical nutrition · Oxford University Press · added 2026-04-24
David Karasik, M Carola Zillikens, Yi-Hsiang Hsu, Ali Aghdassi, Kristina Akesson, Najaf Amin, Inês Barroso, David A Bennett, Lars Bertram, Murielle Bochud, Ingrid B Borecki, Linda Broer, Aron S Buchman, Liisa Byberg, Harry Campbell, Natalia Campos-Obando, Jane A Cauley, Peggy M Cawthon, John C Chambers, Zhao Chen, Nam H Cho, Hyung Jin Choi, Wen-Chi Chou, Steven R Cummings, Lisette C P G M de Groot, Phillip L De Jager, Ilja Demuth, Luda Diatchenko, Michael J Econs, Gudny Eiriksdottir, Anke W Enneman, Joel Eriksson, Johan G Eriksson, Karol Estrada, Daniel S Evans, Mary F Feitosa, Mao Fu, Christian Gieger, Harald Grallert, Vilmundur Gudnason, Launer J Lenore, Caroline Hayward, Albert Hofman, Georg Homuth, Kim M Huffman, Lise B Husted, Thomas Illig, Erik Ingelsson, Till Ittermann, John-Olov Jansson, Toby Johnson, Reiner Biffar, Joanne M Jordan, Antti Jula, Magnus Karlsson, Kay-Tee Khaw, Tuomas O Kilpeläinen, Norman Klopp, Jacqueline S L Kloth, Daniel L Koller, Jaspal S Kooner, William E Kraus, Stephen Kritchevsky, Zoltán Kutalik, Teemu Kuulasmaa, Johanna Kuusisto, Markku Laakso, Jari Lahti, Thomas Lang, Bente L Langdahl, Markus M Lerch, Joshua R Lewis, Christina Lill, Lars Lind, Cecilia Lindgren, Yongmei Liu, Gregory Livshits, Östen Ljunggren, Ruth J F Loos, Mattias Lorentzon, Jian'an Luan, Robert N Luben, Ida Malkin, Fiona E McGuigan, Carolina Medina-Gomez, Thomas Meitinger, Håkan Melhus, Dan Mellström, Karl Michaëlsson, Braxton D Mitchell, Andrew P Morris, Leif Mosekilde, Maria Nethander, Anne B Newman, Jeffery R O'Connell, Ben A Oostra, Eric S Orwoll, Aarno Palotie, Munro Peacock, Markus Perola, Annette Peters, Richard L Prince, Bruce M Psaty, Katri Räikkönen, Stuart H Ralston, Samuli Ripatti, Fernando Rivadeneira, John A Robbins, Jerome I Rotter, Igor Rudan, Veikko Salomaa, Suzanne Satterfield, Sabine Schipf, Chan Soo Shin, Albert V Smith, Shad B Smith, Nicole Soranzo, Timothy D Spector, Alena Stancáková, Kari Stefansson, Elisabeth Steinhagen-Thiessen, Lisette Stolk, Elizabeth A Streeten, Unnur Styrkarsdottir, Karin M A Swart, Patricia Thompson, Cynthia A Thomson, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Emmi Tikkanen, Gregory J Tranah, André G Uitterlinden, Cornelia M Van Duijn, Natasja M van Schoor, Liesbeth Vandenput, Peter Vollenweider, Henry Völzke, Jean Wactawski-Wende, Mark Walker, Nicholas J Wareham, Dawn Waterworth, Michael N Weedon, H-Erich Wichmann, Elisabeth Widen, Frances M K Williams, James F Wilson, Nicole C Wright, Laura M Yerges-Armstrong, Lei Yu, Weihua Zhang, Jing Hua Zhao, Yanhua Zhou, Carrie M Nielson, Tamara B Harris, Serkalem Demissie, Douglas P Kiel, Claes Ohlsson Show less
Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce Show more
Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce the power to identify genetic signals having an association with both lean mass and fat mass. To determine the impact of different fat mass adjustments on genetic architecture of LM and identify additional LM loci. We performed genome-wide association analyses for whole-body LM (20 cohorts of European ancestry with n = 38,292) measured using dual-energy X-ray absorptiometry) or bioelectrical impedance analysis, adjusted for sex, age, age2, and height with or without fat mass adjustments (Model 1 no fat adjustment; Model 2 adjustment for fat mass as a percentage of body mass; Model 3 adjustment for fat mass in kilograms). Seven single-nucleotide polymorphisms (SNPs) in separate loci, including one novel LM locus (TNRC6B), were successfully replicated in an additional 47,227 individuals from 29 cohorts. Based on the strengths of the associations in Model 1 vs Model 3, we divided the LM loci into those with an effect on both lean mass and fat mass in the same direction and refer to those as "sumo wrestler" loci (FTO and MC4R). In contrast, loci with an impact specifically on LM were termed "body builder" loci (VCAN and ADAMTSL3). Using existing available genome-wide association study databases, LM increasing alleles of SNPs in sumo wrestler loci were associated with an adverse metabolic profile, whereas LM increasing alleles of SNPs in "body builder" loci were associated with metabolic protection. In conclusion, we identified one novel LM locus (TNRC6B). Our results suggest that a genetically determined increase in lean mass might exert either harmful or protective effects on metabolic traits, depending on its relation to fat mass. Show less
no PDF DOI: 10.1093/ajcn/nqy272
MC4R

A multi-lock inhibitory mechanism for fine-tuning enzyme activities of the HECT family E3 ligases.

Zhen Wang, Ziheng Liu, Xing Chen +7 more · 2019 · Nature communications · Nature · added 2026-04-24
HECT E3 ligases control the degradation and functioning of numerous oncogenic/tumor-suppressive factors and signaling proteins, and their activities must be tightly regulated to prevent cancers and ot Show more
HECT E3 ligases control the degradation and functioning of numerous oncogenic/tumor-suppressive factors and signaling proteins, and their activities must be tightly regulated to prevent cancers and other diseases. Here we show that the Nedd4 family HECT E3 WWP1 adopts an autoinhibited state, in which its multiple WW domains sequester HECT using a multi-lock mechanism. Removing WW2 or WW34 led to a partial activation of WWP1. The structure of fully inhibited WWP1 reveals that many WWP1 mutations identified in cancer patients result in a partially active state with increased E3 ligase activity, and the WWP1 mutants likely promote cell migration by enhancement of ∆Np63α degradation. We further demonstrate that WWP2 and Itch utilize a highly similar multi-lock autoinhibition mechanism as that utilized by WWP1, whereas Nedd4/4 L and Smurf2 utilize a slightly variant version. Overall, these results reveal versatile autoinhibitory mechanisms that fine-tune the ligase activities of the HECT family enzymes. Show less
no PDF DOI: 10.1038/s41467-019-11224-7
WWP2

N3ICD with the transmembrane domain can effectively inhibit EMT by correcting the position of tight/adherens junctions.

Junyu Tan, Xixun Zhang, Wenjun Xiao +5 more · 2019 · Cell adhesion & migration · Taylor & Francis · added 2026-04-24
EMT allows a polarized epithelium to lose epithelial integrity and acquire mesenchymal characteristics. Previously, we found that overexpression of the intracellular domain of Notch3 (N3ICD) can inhib Show more
EMT allows a polarized epithelium to lose epithelial integrity and acquire mesenchymal characteristics. Previously, we found that overexpression of the intracellular domain of Notch3 (N3ICD) can inhibit EMT in breast cancer cells. In this study, we aimed to elucidate the influence of N3ICD or N3ICD combined with the transmembrane domain (TD+N3ICD) on the expression and distribution of TJs/AJs and polar molecules. We found that although N3ICD can upregulate the expression levels of the above-mentioned molecules, TD+N3ICD can inhibit EMT more effectively than N3ICD alone. TD+N3ICD overexpression upregulated the expression of endogenous full-length Notch3 and contributed to correcting the position of TJs/AJs molecules and better acinar structures formation. Co-immunoprecipitation results showed that the upregulated endogenous full-length Notch3 could physically interact with E-ca in MDA-MB-231/pCMV-(TD+N3ICD) cells. Collectively, our data indicate that overexpression of TD+N3ICD can effectively inhibit EMT, resulting in better positioning of TJs/AJs molecules and cell-cell adhesion in breast cancer cells. Show less
no PDF DOI: 10.1080/19336918.2019.1619958
PATJ

Cell division cycle 20 (CDC20) drives prostate cancer progression via stabilization of β-catenin in cancer stem-like cells.

Qin Zhang, Hai Huang, Ao Liu +7 more · 2019 · EBioMedicine · Elsevier · added 2026-04-24
Cell division cycle 20 (CDC20) is frequently overexpressed in malignant tumours and involved in the differentiation process of hematopoietic stem cells. However, the role of CDC20 in prostate cancer s Show more
Cell division cycle 20 (CDC20) is frequently overexpressed in malignant tumours and involved in the differentiation process of hematopoietic stem cells. However, the role of CDC20 in prostate cancer stem-like cells (CSCs) remains poorly understood. The expression of CDC20, CD44, β-catenin were examined in prostate cancer specimens by immunohistochemistry assay, the role of CDC20 on the stem-like properties of prostate CSCs was accessed by real-time quantitive PCR, spheroid formation, in vitro and in vivo limiting dilution assay. CDC20 was associated with malignant progression of prostate cancer, the patients with both high expression CDC20 and CD44 or β-catenin were associated with more aggressive clinicopathological features and poor prognosis. CDC20 was usually enriched in CD44 Our results indicated that CDC20 maintains the self-renewal ability of CD44 Show less
📄 PDF DOI: 10.1016/j.ebiom.2019.03.032
AXIN1

Tumor Intrinsic Efficacy by SHP2 and RTK Inhibitors in KRAS-Mutant Cancers.

Huai-Xiang Hao, Hongyun Wang, Chen Liu +22 more · 2019 · Molecular cancer therapeutics · added 2026-04-24
no PDF DOI: 10.1158/1535-7163.MCT-19-0170
DUSP6

Variation in the Promoter Region of the

Girmay Shishay, Guiqiong Liu, Xunping Jiang +5 more · 2019 · International journal of molecular sciences · MDPI · added 2026-04-24
The
📄 PDF DOI: 10.3390/ijms20020240
MC4R

Multi-omics Analysis of Microenvironment Characteristics and Immune Escape Mechanisms of Hepatocellular Carcinoma.

Wenli Li, Huimei Wang, Zhanzhong Ma +4 more · 2019 · Frontiers in oncology · Frontiers · added 2026-04-24
The immune environment in primary tumor has a profound impact on immunotherapy. However, the clinical relevance of immune environment in hepatocellular carcinoma (HCC) is largely unknown. Here, the im Show more
The immune environment in primary tumor has a profound impact on immunotherapy. However, the clinical relevance of immune environment in hepatocellular carcinoma (HCC) is largely unknown. Here, the immune profile and its clinical response in HCC were investigated. The gene expression profiles of 569 HCCs from three cohorts (The Cancer Genome Atlas, TCGA, Show less
📄 PDF DOI: 10.3389/fonc.2019.01019
AXIN1

Cholesterol depletion sensitizes gallbladder cancer to cisplatin by impairing DNA damage response.

Yonglong Zhang, Yanfeng Liu, Jinlin Duan +4 more · 2019 · Cell cycle (Georgetown, Tex.) · Taylor & Francis · added 2026-04-24
Gallbladder cancer (GBC) is the common malignancy of the bile tract system with extremely poor clinical outcomes, owing to its metastatic property and intrinsic resistance to the first-line drugs. Alt Show more
Gallbladder cancer (GBC) is the common malignancy of the bile tract system with extremely poor clinical outcomes, owing to its metastatic property and intrinsic resistance to the first-line drugs. Although it is well-established that cholesterol abnormity contributes to gallstone formation, a leading risk factor for GBC, the link of cholesterol homeostasis with GBC has not been investigated. The present study systematically examined the genes implicated in cholesterol homeostasis, and revealed altered gene expressions of Show less
no PDF DOI: 10.1080/15384101.2019.1676581
CETP

[Expression of β-catenin in Skin Lesions of Patients with Scleroderma and Its Effect on Epithelial-Mesenchymal Transition of Human Epidermal Keratinocytes].

Jin-Juan Liu, Hong-Fa Yang, Yong-Jian Li +1 more · 2019 · Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · added 2026-04-24
To investigate the expression of β-catenin in the skin lesions of patients with systemic scleroderma (SSc) and its effect on epithelial-mesenchymal transition (EMT) of human epidermal keratinocytes. T Show more
To investigate the expression of β-catenin in the skin lesions of patients with systemic scleroderma (SSc) and its effect on epithelial-mesenchymal transition (EMT) of human epidermal keratinocytes. The expression of β-catenin, Snail1 and E-cadherin in the skin lesions sample of 45 SSc patients and normal skin sample from 20 healthy adults was detected with SP immunohistochemistry. HaCaT, the human epidermal keratinocytes, were treated with different concentrations of Wnt10b (0 ng/mL (control), 2 ng/mL and 4 ng/mL) for 48 h. then detected the localization of β-catenin in HaCaT cells by immunofluorescence assay, determined the mRNA levels of Snail1 and Snail2 in HaCaT cells by real-time fluorescent quantitative PCR, detected the proteins expression of β-catenin, Vimentin, N-cadherin and E-cadherin in HaCaT cells by Western blot. The positive rates of β-catenin, Snail1 and E-cadherin in skin lesions of SSc patients were 100%, 88.89% and 2.22% respectively, while in healthy adult skin, the corresponding positive rates were 0%, 10.00%, and 95.00%. The difference between the two groups was significant. Compared with control group, treatment with different concentrations of Wnt10b (2 ng/mL and 4 ng/mL) induced up-regulation of β-catenin expression and promoted translocation of β-catenin from cytoplasm to nucleus, increased the mRNA levels of Snail1 and Snail2 ( Abnormally activated Wnt/β-catenin signaling pathway and abnormally expressed EMT-related proteins are observed in SSc lesions. Activation of Wnt/β-catenin signaling pathway may promote EMT in HaCaT cells. Show less
no PDF
SNAI1

Xiaoyaosan Ameliorates Chronic Immobilization Stress-Induced Depression-Like Behaviors and Anorexia in Rats: The Role of the Nesfatin-1-Oxytocin-Proopiomelanocortin Neural Pathway in the Hypothalamus.

Qingyu Ma, Xiaojuan Li, Zhiyi Yan +6 more · 2019 · Frontiers in psychiatry · Frontiers · added 2026-04-24
📄 PDF DOI: 10.3389/fpsyt.2019.00910
MC4R

Genotype-by-environment interaction of fertility traits in Danish Holstein cattle using a single-step genomic reaction norm model.

Zhe Zhang, Morten Kargo, Aoxing Liu +3 more · 2019 · Heredity · Nature · added 2026-04-24
Genotype-by-environment (G × E) interactions could play an important role in cattle populations, and it should be considered in breeding programmes to select the best sires for different environments. Show more
Genotype-by-environment (G × E) interactions could play an important role in cattle populations, and it should be considered in breeding programmes to select the best sires for different environments. The objectives of this study were to study G × E interactions for female fertility traits in the Danish Holstein dairy cattle population using a reaction norm model (RNM), and to detect the particular genomic regions contributing to the performance of these traits and the G × E interactions. In total 4534 bulls were genotyped by an Illumina BovineSNP50 BeadChip. An RNM with a pedigree-based relationship matrix and a pedigree-genomic combined relationship matrix was used to explore the existence of G × E interactions. In the RNM, the environmental gradient (EG) was defined as herd effect. Further, the genomic regions affecting interval from calving to first insemination (ICF) and interval from first to last insemination (IFL) were detected using single-step genome-wide association study (ssGWAS). The genetic correlations between extreme EGs indicated that G × E interactions were sizable for ICF and IFL. The genomic RNM (pedigree-genomic combined relationship matrix) had higher prediction accuracy than the conventional RNM (pedigree-based relationship matrix). The top genomic regions affecting the slope of the reaction norm included immunity-related genes (IL17, IL17F and LIF), and growth-related genes (MC4R and LEP), while the top regions influencing the intercept of the reaction norm included fertility-related genes such as EREG, AREG and SMAD4. In conclusion, our findings validated the G × E interactions for fertility traits across different herds and were helpful in understanding the genetic background of G × E interactions for these traits. Show less
📄 PDF DOI: 10.1038/s41437-019-0192-4
MC4R

Identification of genetic factors underlying persistent pulmonary hypertension of newborns in a cohort of Chinese neonates.

Xu Liu, Mei Mei, Xiang Chen +8 more · 2019 · Respiratory research · BioMed Central · added 2026-04-24
Persistent pulmonary hypertension of the newborn (PPHN) is a severe clinical problem among neonatal intensive care unit (NICU) patients. The genetic pathogenesis of PPHN is unclear. Only a few genetic Show more
Persistent pulmonary hypertension of the newborn (PPHN) is a severe clinical problem among neonatal intensive care unit (NICU) patients. The genetic pathogenesis of PPHN is unclear. Only a few genetic polymorphisms have been identified in infants with PPHN. Our study aimed to investigate the potential genetic etiology of PPHN. This study recruited PPHN patients admitted to the NICU of the Children's Hospital of Fudan University from Jan 2016 to Dec 2017. Exome sequencing was performed for all patients. Variants in reported PPHN/pulmonary arterial hypertension (PAH)-related genes were assessed. Single nucleotide polymorphism (SNP) association and gene-level analyses were carried out in 74 PPHN cases and 115 non-PPHN controls with matched baseline characteristics. Among the patient cohort, 74 (64.3%) patients were late preterm and term infants (≥ 34 weeks gestation) and 41 (35.7%) were preterm infants (< 34 weeks gestation). Preterm infants with PPHN exhibited low birth weight and a high frequency of bronchopulmonary dysplasia, respiratory distress syndrome (RDS) and mortality. Nine patients (only one preterm infant) were identified as harboring genetic variants, including three with pathogenic/likely pathogenic variants in TBX4 and BMPR2 and six with variants of unknown significance in BMPR2, SMAD9, TGFB1, KCNA5 and TRPC6. Three SNPs (rs192759073, rs1047883 and rs2229589) in CPS1 and one SNP (rs1044008) in NOTCH3 were significantly associated with PPHN (p < 0.05). CPS1 and SMAD9 were identified as risk genes for PPHN (p < 0.05). In this study, we identified genetic variants in PPHN patients, and we reported CPS1, NOTCH3 and SMAD9 as risk genes for late preterm and term PPHN in a single-center Chinese cohort. Our findings provide additional genetic evidence of the pathogenesis of PPHN and new insight into potential strategies for disease treatment. Show less
📄 PDF DOI: 10.1186/s12931-019-1148-1
CPS1

Epigallocatechin-3-Gallate Attenuates Adriamycin-Induced Focal Segmental Glomerulosclerosis via Suppression of Oxidant Stress and Apoptosis by Targeting Hypoxia-Inducible Factor-1α/ Angiopoietin-Like 4 Pathway.

Guoyong Liu, Liyu He · 2019 · Pharmacology · added 2026-04-24
Focal and segmental glomerular sclerosis (FSGS) is a common cause of nephrotic syndrome and end-stage renal disease. It has been reported that overproduction of reactive oxygen species (ROS) and cell Show more
Focal and segmental glomerular sclerosis (FSGS) is a common cause of nephrotic syndrome and end-stage renal disease. It has been reported that overproduction of reactive oxygen species (ROS) and cell apoptosis are associated with the development of FSGS. Epigallocatechin-3-gallate (EGCG) is a bioactive constituent accounting for more than 50% of the total catechins in green tea, which have anti-oxidative and anti-apoptotic effects. Based on this, this study was designed to evaluate the renoprotective effect of EGCG treatment on Adriamycin-induced FSGS. -Methods: In C57BL/6 mice, Adriamycin nephropathy (AN) was induced by Adriamycin (10 mg/kg body weight, diluted in normal saline) via a tail vein on day 0. Then the mice were given with EGCG (20 mg/kg body weight) or YC-1 (Lificiguat, a specific inhibitor of hypoxia-inducible factor-1α [HIF-1α], 50 mg/kg body weight) or both intraperitoneally. Both the EGCG and YC-1 were given on the day of Adriamycin injection and continued for 6 weeks. The animals were organized into the following 5 groups for the animal experiments: the control group, the AN group, the AN + EGCG group, the AN + YC-1 group and the AN + EGCG + YC-1 group. At 6 weeks, the mice were sacrificed; kidneys and blood samples were collected for further analysis. The HIF-1α and the angiopoietin-like 4 (ANGPTL4) expression were detected by Western blot, real-time PCR, immunohistochemistry or immunofluorescence. Dihydroethidium staining and NADPH oxidase 1 (Nox1) measurement were used to detect ROS production. Terminal deoxynucleotide transferase-mediated dUTP nick end-labeling (TUNEL) staining and caspase-3 measurement was used to detect cell apoptosis. When the animals were treated with Adriamycin, both the ROS production and TUNEL positive cells increased. Besides, the expression of HIF-1α, ANGPTL4, and caspase-3 were also up-regulated, while EGCG treatment could attenuate these changes. Interestingly, compared with treatment with YC-1 or EGCG alone, more pronounced inhibition of ANGPTL4, caspase-3 and Nox1 were obtained when YC-1 and EGCG were administered simultaneously. EGCG attenuates FSGS through the suppression of Oxidant Stress and apoptosis by targeting the HIF-1α/ANGPTL4 pathway. Show less
no PDF DOI: 10.1159/000496799
ANGPTL4

A Compound Heterozygous Mutation of Lipase Maturation Factor 1 is Responsible for Hypertriglyceridemia of a Patient.

Yihui Liu, Jiang Xu, Wanyun Tao +2 more · 2019 · Journal of atherosclerosis and thrombosis · added 2026-04-24
Dyslipidemia is the most common lipid metabolism disorder in humans, and its etiology remains elusive. Hypertriglyceridemia (HTG) is a type of dyslipidemia that contributes to atherosclerosis and coro Show more
Dyslipidemia is the most common lipid metabolism disorder in humans, and its etiology remains elusive. Hypertriglyceridemia (HTG) is a type of dyslipidemia that contributes to atherosclerosis and coronary heart disease. Previous studies have demonstrated that mutations in lipoprotein lipase (LPL), apolipoprotein CII (APOC2), apolipoprotein AV (APOA5), glycosylphosphatidylinositol anchored high-density lipoprotein-binding protein 1 (GPIHBP1), lipase maturation factor 1(LMF1), and glycerol-3 phosphate dehydrogenase 1 (GPD1) are responsible for HTG by using genomic microarrays and next-generation sequencing. The aim of this study was to identify genetic lesions in patients with HTG. Our study included a family of seven members from Jiangsu province across three generations. The proband was diagnosed with severe HTG, with a plasma triglyceride level of 38.70 mmol/L. Polymerase chain reaction (PCR) and Sanger sequencing were performed to explore the possible causative gene mutations for this patient. Furthermore, we measured the post-heparin LPL and hepatic lipase (HL) activities using an antiserum inhibition method. A compound heterozygous mutation in the LMF1 gene (c.257C＞T/p.P86L and c.1184C＞T/p.T395I) was identified and co-segregated with the affected patient in this family. Both mutations were predicted to be deleterious by three bioinformatics programs (Polymorphism Phenotyping-2, Sorting Intolerant From Tolerant, and MutationTaster). The levels of the plasma post-heparin LPL and HL activities in the proband (57 and 177 mU/mL) were reduced to 24% and 75%, respectively, compared with those assayed in the control subject with normal plasma triglycerides. A compound heterozygous mutation of LMF1 was identified in the presenting patient with severe HTG. These findings expand on the spectrum of LMF1 mutations and contribute to the genetic diagnosis and counseling of families with HTG. Show less
📄 PDF DOI: 10.5551/jat.44537
APOA5

Dysregulated expressions of PTEN, NF-κB, WWP2, p53 and c-Myc in different subtypes of B cell lymphoma and reactive follicular hyperplasia.

Huan Fu, Chenghao Jin, Qingxiu Zhu +4 more · 2019 · American journal of translational research · added 2026-04-24
This study aimed to investigate the value of PTEN, NF-κB, WWP2, p53 and c-Myc expressions in distinguishing B cell lymphomas from reactive follicular hyperplasia (RFH), and their abilities to discrimi Show more
This study aimed to investigate the value of PTEN, NF-κB, WWP2, p53 and c-Myc expressions in distinguishing B cell lymphomas from reactive follicular hyperplasia (RFH), and their abilities to discriminate different B cell lymphoma subtypes. Lymphoma tissue samples were obtained from 30 follicular lymphoma (FL) patients, 30 germinal center B-cell like (GCB) diffuse large B cell lymphoma (DLBCL) patients, 30 non-GCB DLBCL patients and 30 Burkitt's lymphoma (BL) patients. And hyperplasia tissue samples were obtained from and 30 RFH patients. Immunohistochemistry was used to quantify the expressions of PTEN, NF-κB, WWP2, P53 and c-Myc. PTEN expression was elevated in GCB DLBCL and BL compared with RFH, and in GCB DLBCL, non-GCB DLBCL and BL than that in FL; WWP2 expression was higher in FL, GCB DLBCL, non-GCB DLBCL and BL compared with RFH; p53 expression increased in non-GCB DLBCL compared with RFH, and in BL compared with RFH, FL or GCB DLBCL; c-Myc expression was higher in GCB DLBCL, non-GCB DLBCL and BL compared with RFH; c-Myc expression was elevated in GCB DLBCL, non-GCB DLBCL and BL compared with FL. Additionally, PTEN negatively correlated with p53 expression in FL and CGB DLBCL, whereas NF-κB negatively correlated with WWP2 in GCB DLBCL, but positively associated with PTEN in RFH and c-Myc in BL. PTEN, WWP2, p53 and c-Myc expressions might be served as biomarkers for identification of B cell lymphomas from RFH as well as distinguishing different B cell lymphoma subtypes. Show less
no PDF
WWP2

Engineering Microbial Consortia for High-Performance Cellulosic Hydrolyzates-Fed Microbial Fuel Cells.

Feng Li, Xingjuan An, Deguang Wu +9 more · 2019 · Frontiers in microbiology · Frontiers · added 2026-04-24
Microbial fuel cells (MFCs) are eco-friendly bio-electrochemical reactors that use exoelectrogens as biocatalyst for electricity harvest from organic biomass, which could also be used as biosensors fo Show more
Microbial fuel cells (MFCs) are eco-friendly bio-electrochemical reactors that use exoelectrogens as biocatalyst for electricity harvest from organic biomass, which could also be used as biosensors for long-term environmental monitoring. Glucose and xylose, as the primary ingredients from cellulose hydrolyzates, is an appealing substrate for MFC. Nevertheless, neither xylose nor glucose can be utilized as carbon source by well-studied exoelectrogens such as Show less
📄 PDF DOI: 10.3389/fmicb.2019.00409
CPS1

A transcriptome-wide association study of high-grade serous epithelial ovarian cancer identifies new susceptibility genes and splice variants.

Alexander Gusev, Kate Lawrenson, Xianzhi Lin +16 more · 2019 · Nature genetics · Nature · added 2026-04-24
We sought to identify susceptibility genes for high-grade serous ovarian cancer (HGSOC) by performing a transcriptome-wide association study of gene expression and splice junction usage in HGSOC-relev Show more
We sought to identify susceptibility genes for high-grade serous ovarian cancer (HGSOC) by performing a transcriptome-wide association study of gene expression and splice junction usage in HGSOC-relevant tissue types (N = 2,169) and the largest genome-wide association study available for HGSOC (N = 13,037 cases and 40,941 controls). We identified 25 transcriptome-wide association study significant genes, 7 at the junction level only, including LRRC46 at 19q21.32, (P = 1 × 10 Show less
📄 PDF DOI: 10.1038/s41588-019-0395-x
KANSL1

Targeting BCAA Catabolism to Treat Obesity-Associated Insulin Resistance.

Meiyi Zhou, Jing Shao, Cheng-Yang Wu +17 more · 2019 · Diabetes · added 2026-04-24
Recent studies implicate a strong association between elevated plasma branched-chain amino acids (BCAAs) and insulin resistance (IR). However, a causal relationship and whether interrupted BCAA homeos Show more
Recent studies implicate a strong association between elevated plasma branched-chain amino acids (BCAAs) and insulin resistance (IR). However, a causal relationship and whether interrupted BCAA homeostasis can serve as a therapeutic target for diabetes remain to be established experimentally. In this study, unbiased integrative pathway analyses identified a unique genetic link between obesity-associated IR and BCAA catabolic gene expression at the pathway level in human and mouse populations. In genetically obese ( Show less
📄 PDF DOI: 10.2337/db18-0927
BCKDK

Precision Health Resource of Control iPSC Lines for Versatile Multilineage Differentiation.

Matthew R Hildebrandt, Miriam S Reuter, Wei Wei +25 more · 2019 · Stem cell reports · Elsevier · added 2026-04-24
Induced pluripotent stem cells (iPSC) derived from healthy individuals are important controls for disease-modeling studies. Here we apply precision health to create a high-quality resource of control Show more
Induced pluripotent stem cells (iPSC) derived from healthy individuals are important controls for disease-modeling studies. Here we apply precision health to create a high-quality resource of control iPSCs. Footprint-free lines were reprogrammed from four volunteers of the Personal Genome Project Canada (PGPC). Multilineage-directed differentiation efficiently produced functional cortical neurons, cardiomyocytes and hepatocytes. Pilot users demonstrated versatility by generating kidney organoids, T lymphocytes, and sensory neurons. A frameshift knockout was introduced into MYBPC3 and these cardiomyocytes exhibited the expected hypertrophic phenotype. Whole-genome sequencing-based annotation of PGPC lines revealed on average 20 coding variants. Importantly, nearly all annotated PGPC and HipSci lines harbored at least one pre-existing or acquired variant with cardiac, neurological, or other disease associations. Overall, PGPC lines were efficiently differentiated by multiple users into cells from six tissues for disease modeling, and variant-preferred healthy control lines were identified for specific disease settings. Show less
no PDF DOI: 10.1016/j.stemcr.2019.11.003
MYBPC3

Comparative transcriptome analysis reveals regulators mediating breast muscle growth and development in three chicken breeds.

Zengrong Zhang, Huarui Du, Chaowu Yang +12 more · 2019 · Animal biotechnology · Taylor & Francis · added 2026-04-24
no PDF DOI: 10.1080/10495398.2018.1476377
MYBPC3

Meningitic

Lu Liu, Jixuan Li, Dong Huo +7 more · 2019 · Pathogens (Basel, Switzerland) · MDPI · added 2026-04-24
Bacterial meningitis is currently recognized as one of the most important life-threatening infections of the central nervous system (CNS) with high morbidity and mortality, despite the advancements in Show more
Bacterial meningitis is currently recognized as one of the most important life-threatening infections of the central nervous system (CNS) with high morbidity and mortality, despite the advancements in antimicrobial treatment. The disruption of blood-brain barrier (BBB) induced by meningitis bacteria is crucial for the development of bacterial meningitis. However, the complete mechanisms involving in the BBB disruption remain to be elucidated. Here, we found meningitic Show less
📄 PDF DOI: 10.3390/pathogens8040254
ANGPTL4

Molecular identification and function analysis of bactericidal permeability-increasing protein/LPS-binding protein 1 (BPI/LBP1) from turbot (Scophthalmus maximus).

Shun Zhou, Guangpeng Jiang, Ying Zhu +5 more · 2019 · Fish & shellfish immunology · Elsevier · added 2026-04-24
Bactericidal permeability-increasing protein (BPI) and lipopolysaccharide-binding protein (LBP) play important roles in host antimicrobial defense. In the present study, we identified one isoform of B Show more
Bactericidal permeability-increasing protein (BPI) and lipopolysaccharide-binding protein (LBP) play important roles in host antimicrobial defense. In the present study, we identified one isoform of BPI/LBP gene from turbot (Scophthalmus maximus), designated as SmBPI/LBP1. The full-length cDNA sequence of SmBPI/LBP1 was 1826 bp, which encoding one secreted protein with 480 amino acid residues. Structurally, the SmBPI/LBP1 showed high similarity to its homologs from other vertebrates or invertebrates, which all contained a signal peptide, a BPI/LBP/CETP N-terminal with a LPS-binding domain, and a BPI/LBP/CETP C-terminal domain. The deduced amino acid sequences of SmBPI/LBP1 shared significant similarity to BPI/LBP of Seriola lalandi dorsalis (71%) and Paralichthys olivaceus (69%). Phylogentic analysis further supported that SmBPI/LBP1 act as a new member of vertebrate BPI/LBP family. SmBPI/LBP1 was ubiquitously expressed in all tested tissues, with the highest expression level in spleen tissue. The mRNA expression of SmBPI/LBP1 in spleen and kidney were significantly up-regulated after Vibrio vulnificus challenge. Finally, the recombinant SmBPI/LBP1 showed high affinity to lipopolysaccharide, followed by peptidoglycan and lipoteichoic acid, which is the ubiquitous component of Gram-negative or Gram-positive bacteria. These results indicated that SmBPI/LBP1 probably played important roles in immune response against bacteria infection. Show less
no PDF DOI: 10.1016/j.fsi.2019.02.004
CETP

Identification of Differentially Expressed Genes and Pathways for Abdominal Fat Deposition in Ovariectomized and Sham-Operated Chickens.

Xiaopeng Mu, Xiaoyan Cui, Ranran Liu +7 more · 2019 · Genes · MDPI · added 2026-04-24
Ovariectomy results in improved meat quality (growth rate, tenderness, and flavor) of broilers. However, some negative effects increased (abdominal fat (AF) deposition, low feed conversion, etc.) have Show more
Ovariectomy results in improved meat quality (growth rate, tenderness, and flavor) of broilers. However, some negative effects increased (abdominal fat (AF) deposition, low feed conversion, etc.) have also been reported. In this study, the gene expression profiles of AF tissue in ovariectomized and sham-operated chickens were determined to identify differentially expressed genes (DEGs) and pathways to explore the molecular mechanisms underlying AF accumulation. Comparing the ovariectomized group and the sham-operated group, the abdominal fat weight (AFW) and abdominal fat percentage (AFP) were increased significantly ( Show less
📄 PDF DOI: 10.3390/genes10020155
CETP

RNA-Binding Motif Protein 6 is a Candidate Serum Biomarker for Pancreatic Cancer.

Baojun Duan, Xiaoyan Hu, Meiyang Fan +9 more · 2019 · Proteomics. Clinical applications · Wiley · added 2026-04-24
Early diagnosis is crucial to improve outcomes for pancreatic cancer patients (PC). The present study is designed to identify differently expressed peptides involved in PC as potential biomarkers. The Show more
Early diagnosis is crucial to improve outcomes for pancreatic cancer patients (PC). The present study is designed to identify differently expressed peptides involved in PC as potential biomarkers. The serum proteome of 22 PC patients, 12 pancreatitis patients (PP), and 45 healthy controls (HC) are analyzed using magnetic bead-based weak cation exchange (MB-WCX) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Next, a supervised neural network (SNN) algorithm model is established by ClinProTools and the candidate biomarker identified using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Finally, the candidate biomarker is validated in tissue samples. The SNN algorithm model discriminates PC from HC with 92.97% sensitivity and 94.55% specificity. Seventy-six differentially expressed peptides are identified, seven of which are significantly different among PC, PP, and HC (p < 0.05). Only one peak (m/z: 1466.99) tends to be upregulated in samples from HC, PP, and PC, which is identified as region of RNA-binding motif protein 6 (RBM6). In subsequent tissue analysis, it is verified that RBM6 expression is significantly higher in PC tissues than paracancerous tissue. The results indicate that RBM6 might serve as a candidate diagnostic biomarker for PC. Methods used in this study could generate serum peptidome profiles of PC, PP, and HC, and present an approach to identify potential biomarkers for diagnosis of this malignancy. Show less
no PDF DOI: 10.1002/prca.201900048
RBM6

Whole Genome Analyses of Chinese Population and De Novo Assembly of A Northern Han Genome.

Zhenglin Du, Liang Ma, Hongzhu Qu +27 more · 2019 · Genomics, proteomics & bioinformatics · Elsevier · added 2026-04-24
To unravel the genetic mechanisms of disease and physiological traits, it requires comprehensive sequencing analysis of large sample size in Chinese populations. Here, we report the primary results of Show more
To unravel the genetic mechanisms of disease and physiological traits, it requires comprehensive sequencing analysis of large sample size in Chinese populations. Here, we report the primary results of the Chinese Academy of Sciences Precision Medicine Initiative (CASPMI) project launched by the Chinese Academy of Sciences, including the de novo assembly of a northern Han reference genome (NH1.0) and whole genome analyses of 597 healthy people coming from most areas in China. Given the two existing reference genomes for Han Chinese (YH and HX1) were both from the south, we constructed NH1.0, a new reference genome from a northern individual, by combining the sequencing strategies of PacBio, 10× Genomics, and Bionano mapping. Using this integrated approach, we obtained an N50 scaffold size of 46.63 Mb for the NH1.0 genome and performed a comparative genome analysis of NH1.0 with YH and HX1. In order to generate a genomic variation map of Chinese populations, we performed the whole-genome sequencing of 597 participants and identified 24.85 million (M) single nucleotide variants (SNVs), 3.85 M small indels, and 106,382 structural variations. In the association analysis with collected phenotypes, we found that the T allele of rs1549293 in KAT8 significantly correlated with the waist circumference in northern Han males. Moreover, significant genetic diversity in MTHFR, TCN2, FADS1, and FADS2, which associate with circulating folate, vitamin B12, or lipid metabolism, was observed between northerners and southerners. Especially, for the homocysteine-increasing allele of rs1801133 (MTHFR 677T), we hypothesize that there exists a "comfort" zone for a high frequency of 677T between latitudes of 35-45 degree North. Taken together, our results provide a high-quality northern Han reference genome and novel population-specific data sets of genetic variants for use in the personalized and precision medicine. Show less
📄 PDF DOI: 10.1016/j.gpb.2019.07.002
FADS1

Evaluation of the association of

Ke Liu, Li Ma, Timothy Y Y Lai +5 more · 2019 · Eye and vision (London, England) · BioMed Central · added 2026-04-24
Neovascular age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) are sight-threatening maculopathies with both environmental and genetic risk factors. We have previously Show more
Neovascular age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) are sight-threatening maculopathies with both environmental and genetic risk factors. We have previously shown relative risks posed by genes of the complement pathways to neovascular AMD and PCV. In this study, we investigated the haplotype-tagging single nucleotide polymorphisms (SNPs) in the The results revealed none of the six tagging SNPs of the This study showed no statistical significance in the genetic association of Show less
📄 PDF DOI: 10.1186/s40662-019-0161-2
CETP

Genetic variants in ELOVL2 and HSD17B12 predict melanoma-specific survival.

Wei Dai, Hongliang Liu, Xinyuan Xu +10 more · 2019 · International journal of cancer · Wiley · added 2026-04-24
Fatty acids play a key role in cellular bioenergetics, membrane biosynthesis and intracellular signaling processes and thus may be involved in cancer development and progression. In the present study, Show more
Fatty acids play a key role in cellular bioenergetics, membrane biosynthesis and intracellular signaling processes and thus may be involved in cancer development and progression. In the present study, we comprehensively assessed associations of 14,522 common single-nucleotide polymorphisms (SNPs) in 149 genes of the fatty-acid synthesis pathway with cutaneous melanoma disease-specific survival (CMSS). The dataset of 858 cutaneous melanoma (CM) patients from a published genome-wide association study (GWAS) by The University of Texas M.D. Anderson Cancer Center was used as the discovery dataset, and the identified significant SNPs were validated by a dataset of 409 CM patients from another GWAS from the Nurses' Health and Health Professionals Follow-up Studies. We found 40 noteworthy SNPs to be associated with CMSS in both discovery and validation datasets after multiple comparison correction by the false positive report probability method, because more than 85% of the SNPs were imputed. By performing functional prediction, linkage disequilibrium analysis, and stepwise Cox regression selection, we identified two independent SNPs of ELOVL2 rs3734398 T>C and HSD17B12 rs11037684 A>G that predicted CMSS, with an allelic hazards ratio of 0.66 (95% confidence interval = 0.51-0.84 and p = 8.34 × 10 Show less
📄 PDF DOI: 10.1002/ijc.32194
HSD17B12

Panoramic view of common fusion genes in a large cohort of Chinese de novo acute myeloid leukemia patients.

Xue Chen, Fang Wang, Yang Zhang +9 more · 2019 · Leukemia & lymphoma · Taylor & Francis · added 2026-04-24
Fusion genes are major molecular biological abnormalities in hematological malignancies. This study aimed to depict the common recurrent gene-fusion landscape in acute myeloid leukemia (AML). 3135 de Show more
Fusion genes are major molecular biological abnormalities in hematological malignancies. This study aimed to depict the common recurrent gene-fusion landscape in acute myeloid leukemia (AML). 3135 de novo AML cases were enrolled and 36 recurrent fusion genes were assessed using multiplex-nested RT-PCR. Twenty-three distinct fusion genes were detected in 1292 (41.21%) cases. The incidence of fusion genes was higher in pediatric AML than in adult cases. The pediatric patients had higher incidences of RUNX1-RUNX1T1, KMT2A-MLLT3, KMT2A-MLLT10, KMT2A-MLLT11, KMT2A-MLLT6, and FUS-ERG, whereas KMT2A-PTD was more common in adult patients. The occurrence of molecular abnormalities involving the KMT2A gene and CBFB-MYH11 was lower in Chinese pediatric AML compared to Western reports. The incidence of RUNX1-RUNX1T1 was higher in both pediatric and adult patients in our study than in Western countries. This study provides a genetic landscape of common fusion genes in Chinese AML and confirms different incidences between age groups and races. Show less
no PDF DOI: 10.1080/10428194.2018.1516876
MLLT10