👤 Fei Li

🔍 Search 📋 Browse 🏷️ Tags ❤️ Favourites ➕ Add 🧬 Extraction
3991
Articles
2551
Name variants
Also published as: Xiaofeng Li, Jingwen Li, Jiajia Li, Zhaolun Li, Litao Li, Ruyi Li, Xiaocun Li, Jianyu Li, Wanxin Li, Jinsong Li, Xinzhi Li, Guanqiao Li, Ying-Lan Li, Zequn Li, Yulin Li, Shaojian Li, Guang-Xi Li, Yubo Li, Bugao Li, Mohan Li, Yan-Xue Li, Qingchao Li, Xikun Li, Enhong Li, Hong-Tao Li, Guobin Li, Xiangnan Li, Yong-Jun Li, Hang Li, Rongqing Li, Xihao Li, Ziming Li, Jing-Ming Li, Chang-Da Li, Meng-Yue Li, Yuanchang Li, DaZhuang Li, Xiao-Lin Li, Yicun Li, Zhao-Yang Li, Jiajie Li, Shunqin Li, Xinjia Li, K-L Li, Yaqiong Li, Bin Li, Yuan-hao Li, Jianhai Li, Youran Li, Peiwu Li, Yongmei Li, Changyu Li, Ran Li, Peilin Li, X Y Li, Chunshan Li, Yixiang Li, Ming Zhou Li, Guanglve Li, Z Li, Ye Li, Zili Li, Xinmei Li, Yihao Li, Liling Li, Qing Run Li, Wulan Li, Meng-Yang Li, Ziyun Li, Haoxian Li, Xiaozhao Li, Jun-Ying Li, Da-Lei Li, Xinhai Li, Yongjiang Li, Wanru Li, Jinming Li, Huihui Li, Wenhao Li, Qiankun Li, Kailong Li, Shengxu Li, Shisheng Li, Sai Li, Guangwen Li, Xiuli Li, Hua Li, Yulong Li, Dongmei Li, Ru-Hao Li, Lanzhou Li, Zhi-Peng Li, Tingsong Li, Binjun Li, Chen Li, Yawei Li, Jiayang Li, Zunjiang Li, Chao Bo Li, Minglong Li, Donghua Li, Wenzhe Li, Siming Li, Fengli Li, Song Li, Zihan Li, Hsin-Hua Li, Jin-Long Li, Hongxin Li, Dongfeng Li, You Li, Xuelin Li, Fa-Hui Li, Caiyu Li, Xueyang Li, Zhen-Yuan Li, Guangpu Li, Teng Li, Wen-Jie Li, Ang Li, Hegen Li, Zhizong Li, Lu-Yun Li, Peng Li, Shiyu Li, Bao Li, Yin Li, Cai-Hong Li, Fang Li, Jiuke Li, Miyang Li, Chen-Xi Li, Mingxu Li, Panlong Li, Changwei Li, Dejun Li, Biyu Li, Yufeng Li, Miaoxin Li, San-Feng Li, Yaoqi Li, Hu Li, Bei Li, Sha Li, W H Li, Jiaming Li, Jiyuan Li, Ya-Qiang Li, Rongkai Li, Yani Li, Xiushen Li, Xiaoqing Li, Jinlin Li, Linke Li, C Y Li, Shuaicheng Li, Thomas Li, Siting Li, Xuebiao Li, Yingyi Li, Yongnan Li, Maolin Li, Jiyang Li, Jinchen Li, Jin-Ping Li, Zhongxuan Li, Xuewen Li, R Li, Xianlong Li, Aixin Li, Linting Li, Zhong-Xin Li, Xuening Li, Enhao Li, Guang Li, Xiaoming Li, Shengliang Li, Yongli Li, Z-H Li, Baohong Li, Hujie Li, Yue-Ming Li, Shuyuan Li, L Li, Zhaohan Li, Yuanmei Li, Alexander Li, Yanwu Li, Wen-juan Li, Hualing Li, Sibing Li, Qinghe Li, Xining Li, Pilong Li, Yun-Peng Li, Zonghua Li, C X Li, Jingya Li, Liqin Li, Huanan Li, Youjun Li, Zheng-Dao Li, Miao X Li, Zhenshu Li, KeZhong Li, Heng-Zhen Li, Linying Li, Chu-Qiao Li, Fa-Hong Li, Changzheng Li, Yuhui Li, Wen-Ying Li, Wei Li, Yaokun Li, Shuanglong Li, Zhi-Gang Li, Yufan Li, Liangqian Li, Guanghui Li, Xiongfeng Li, Fei-feng Li, Letai Li, Ming Li, Kangli Li, Wenbo Li, Runwen Li, Yarong Li, Side Li, S E Li, Timmy Li, Weidong Li, Xin-Tao Li, Ruotong Li, Xiuzhen Li, Shuguang Li, Chuan-Hai Li, Lingxi Li, Qiuya Li, Jiezhen Li, Haitao Li, Tingting Li, Guanghua Li, Yufen Li, Qin Li, Zhongyu Li, Deyu Li, Zhen-Yu Li, Hansen Li, Annie Li, Wenge Li, Jinzhi Li, Xueren Li, Chun-Mei Li, Yijing Li, Kaifeng Li, Wen-Xing Li, Meng-Yao Li, Chung-I Li, Zhi-Bin Li, Qintong Li, Junping Li, Xiao Li, PeiQi Li, Naishi Li, Xiaobing Li, Liangdong Li, Xin-Ping Li, Yan Li, Han-Ni Li, Shengchao A Li, Pan Li, Jiaying Li, Jun-Jie Li, Ruonan Li, Cui-lan Li, Shuhao Li, Ruitong Li, Huiqiong Li, Guigang Li, Lucia M Li, Chunzhu Li, Chengquan Li, Suyan Li, Zexu Li, Gen-Lin Li, Dianjie Li, Zhilei Li, Junhui Li, Tiantian Li, Xue Cheng Li, Ya-Jun Li, Wenyong Li, Ding-Biao Li, Tianjun Li, Desen Li, Yansong Li, Xiying Li, Weiyong Li, Zihao Li, Xinyang Li, Fadi Li, Huawei Li, Yu-quan Li, Cui Li, Xiaoyong Li, Y L Li, Xueyi Li, Jingxiang Li, Wenxue Li, Jihua Li, Jingping Li, Zhiquan Li, Zeyu Li, Jianglin Li, Yingpu Li, Jing-Yao Li, Yan-Hua Li, Zongdi Li, Ming V Li, Shawn Shun-Cheng Li, Aowen Li, Xiao-Min Li, L K Li, Ya-Ting Li, Wan Jie Li, Aimin Li, Dongbiao Li, Tiehua Li, Keguo Li, Yuanfei Li, Longhui Li, Jing-Yi Li, Zhonghua Li, Guohong Li, Chunyi Li, Botao Li, Peiyun Li, L-Y Li, Xiuqi Li, Qinglan Li, Zhenhua Li, Zhengda Li, Haotong Li, Yue-Ting Li, Luhan Li, Da Li, Yuancong Li, Tian Li, YiPing Li, Yuxiu Li, Beibei Li, Haipeng Li, Demin Li, Chuan Li, Ze-An Li, Changhong Li, Jianmin Li, Yu Li, Minhui Li, Yvonne Li, Yiwei Li, Xiangzhe Li, Jiayuan Li, Zhichao Li, Siguang Li, Minglun Li, Yige Li, Chengqian Li, Weiye Li, Xue-Min Li, Kenneth Kai Wang Li, Dong-fei Li, Xiangchun Li, Chiyang Li, Chunlan Li, Hulun Li, Juan-Juan Li, Hua-Zhong Li, Hailong Li, Kun-Peng Li, Jiaomei Li, Haijun Li, Si Li, Xiangyun Li, Jing Li, Ji-Feng Li, Yingshuo Li, Wanqian Li, Baixing Li, Zijing Li, Dengke Li, Wentao Li, Yuchuan Li, Qingling Li, Rui-Han Li, Xuhong Li, Hongyun Li, Dong Li, Zhonggen Li, Xiong Li, Penghui Li, Xiaoxia Li, Dezhi Li, Huiting Li, Xiaolong Li, Linqing Li, Jiawei Li, Sheng-Jie Li, Defa Li, Ying-Qing Li, X L Li, Yuyan Li, Kawah Li, Xin-Jian Li, Guangxi Li, Yanhui Li, Zhenfei Li, Shupeng Li, Sha-Sha Li, Gang Li, Mengxuan Li, Panyuan Li, Ziyu Li, Hong-Wen Li, Zhuo Li, Han-Wei Li, Xiaojuan Li, Weina Li, Xiao-Hui Li, Huaiyuan Li, Dongnan Li, Rui-Fang Li, Jianzhong Li, Ji-Liang Li, Huaping Li, C H Li, Bohua Li, Bing Li, Pei-Ying Li, Huihuang Li, Shaobin Li, Yunmin Li, Yanying Li, Ronald Li, Gui Lin Li, Chenrui Li, Shilun Li, Shi-Hong Li, Xinyu Li, John Zhong Li, Lujiao Li, Song-Chao Li, Chenghong Li, Dengfeng Li, Nianfu Li, Baohua Li, N Li, Xiaotong Li, Chensheng Li, Ming-Qing Li, Yongxue Li, Bao-Shan Li, Jiao Li, Zhimei Li, Jun-Cheng Li, Yimeng Li, Jingming Li, Jinxia Li, De-Tao Li, Chunting Li, Shu Li, Julia Li, Chien-Feng Li, Huilan Li, Mei-Zhen Li, Xin-Ya Li, Zhengjie Li, Chunsheng Li, Liwei Li, Yan-Yan Li, Huijun Li, Chengyun Li, Chengjian Li, Ying-na Li, Guihua Li, Zhiyuan Li, Supeng Li, Lijun Li, Hening Li, Yiju Li, Yuanhe Li, Guangxiao Li, Fengxia Li, Peixin Li, Xueqin Li, Feng-Feng Li, Jialing Li, Zu-Ling Li, Xin Li, Yunjiu Li, Zonghong Li, Dayong Li, Ningyan Li, Lingjiang Li, Yuhan Li, Zhenghui Li, Fuyuan Li, Ailing Li, H-F Li, Chaochen Li, Chunxia Li, Zhen-Li Li, Tengyan Li, Xianlu Li, Jiaqi Li, Jiabei Li, Zhengying Li, Yali Li, Zhaoshui Li, Wenjing Li, Yu-Hui Li, Jingshu Li, Chuang Li, Jiajun Li, Can Li, Zhe Li, Han-Bo Li, Stephen Li, Shuangding Li, Zengyang Li, Kaiyuan Li, Mangmang Li, Chunyan Li, Runzhen Li, Xiaopeng Li, Xi-Hai Li, MengGe Li, Xuezhong Li, Anan Li, Luying Li, Jiajv Li, Pei-Lin Li, Xiaoquan Li, Ruobing Li, Yanxi Li, Wan-Xin Li, Ning Li, Meitao Li, Xia Li, Yongjing Li, Huayao Li, Ziqiang Li, Wen-Xi Li, Shenghao Li, Jiqing Li, Boxuan Li, Huixue Li, Hehua Li, Yucheng Li, Qingyuan Li, Yongqi Li, Fengqi Li, Zhigang Li, Yuqing Li, Guiyang Li, Guo-Qiang Li, Dujuan Li, Yanbo Li, Yuying Li, Shaofei Li, Sanqiang Li, Shaoguang Li, Hongyu Li, Min-Rui Li, Guangping Li, Shuqiang Li, Dan C Li, Huashun Li, Jinxin Li, Ganggang Li, Xinrong Li, Haoqi Li, Yayu Li, Handong Li, Huaixing Li, Yan-Nan Li, Xianglong Li, Minyue Li, Hong-Mei Li, Jing-Jing Li, Songhan Li, Mengxia Li, Jutang Li, Conglin Li, Qingli Li, Yongxiang Li, Miao Li, Songlin Li, Qilong Li, Dijie Li, Chenyu Li, Yizhe Li, Ke Li, Yan Bing Li, Jiani Li, Lianjian Li, Yiliang Li, Zhen-Hua Li, Chuan-Yun Li, Xinpeng Li, Hongxing Li, Wanyi Li, Gaoyuan Li, Mi Li, Youming Li, Dong-Yun Li, Qingrun Li, Guo Li, Jingxia Li, Xiu-Ling Li, Fuhai Li, Ruijia Li, Shuangfei Li, Yumiao Li, Fengfeng Li, Qinggang Li, Jiexi Li, Huixia Li, Kecheng Li, Xiangjun Li, Junxu Li, Xingye Li, Junya Li, Jiang Li, Huiying Li, Shengxian Li, Qingyang Li, Yuxi Li, Xiao-Dong Li, Chenxuan Li, Xinghuan Li, Zhaoping Li, Xingyu Li, Xiaolei Li, Zhenlu Li, Wenying Li, Huilong Li, Xiao-Gang Li, Honghui Li, Zhenhui Li, Cheung Li, Zhenming Li, Xuelian Li, Shu-Fen Li, Chunjun Li, Changyan Li, Yinghua Li, Mulin Jun Li, Shangjia Li, Yanjie Li, Jingjing Li, Suhong Li, Xinping Li, Siyu Li, Chaoying Li, Juanjuan Li, Qiu Li, Xiangyan Li, Guangzhen Li, Kunlun Li, Xiaoyu Li, Shiyun Li, Yaobo Li, Shiquan Li, Xuewang Li, Mei Li, Xiangdong Li, Zhenjia Li, Jifang Li, Wan Li, Manjiang Li, Zhizhong Li, Ding Yang Li, Xiao-Li Li, Xiaoya Li, Shan Li, Shitao Li, Lijia Li, Zehan Li, Chunqiong Li, Huiliang Li, Junjun Li, Chenlong Li, Shujin Li, Hui-Long Li, Zhao-Cong Li, Zhi-Wei Li, Wenxi Li, Weining Li, Wu-Jun Li, Chang-hai Li, Bin-Kui Li, Yumao Li, Yuqiu Li, Honglian Li, Xue-Yan Li, Ya-Zhou Li, Yuan-Yuan Li, Xiang-Jun Li, Hongyi Li, Chia Li, Y X Li, Yunyun Li, Zhen-Jia Li, Fu-Rong Li, Honghua Li, Lanjuan Li, Qiuxuan Li, Xiancheng Li, Man-Zhi Li, Yanmei Li, De-Jun Li, Junxian Li, Zhihua Li, Keqing Li, Shuwen Li, Saijuan Li, Minqi Li, Danxi Li, Lingjun Li, Mimi Li, Si-Xing Li, Deheng Li, Yingjie Li, Yaodong Li, Shigang Li, Yuan-Hai Li, Lujie Li, Minghao Li, Gao-Fei Li, Minle Li, Meifen Li, Yifeng Li, Le-Le Li, Huanqing Li, Ziwen Li, Yuhang Li, Yongqiu Li, Pu-Yu Li, Jianhua Li, Nan-Nan Li, Chanjuan Li, Hongming Li, Lan-Lan Li, Shuang Li, Lingyi Li, Yanchuan Li, Wanting Li, Bai-Qiang Li, Gong-Hua Li, Zhengyu Li, Chunmiao Li, Jiong-Ming Li, Yongqiang Li, Linsheng Li, Weiguang Li, Mingyao Li, Guoqing Li, Ze Li, Xiaomeng Li, R H L Li, Yuanze Li, Yunqi Li, Yuandong Li, Guisen Li, Jinglin Li, Dongyang Li, Mingfang Li, Honglong Li, Hanmei Li, Chenmeng Li, Changcheng Li, Shiyang Li, Shiyue Li, Hanbo Li, Jianing Li, Dingshan Li, Yinggao Li, Linlin Li, Xinsheng Li, Jin-Wei Li, Jin-Jiang Li, Cheng-Tian Li, Chang Li, Zhi-Xing Li, Yaxi Li, Ming-Han Li, Wei-Ming Li, Wenchao Li, Guangyan Li, Zhaosha Li, Xuesong Li, Jiwei Li, Yongzhen Li, Chun-Quan Li, Weifeng Li, Tao Li, Wenhui Li, Sichen Li, Xiankai Li, Qingsheng Li, Yaxuan Li, Liangji Li, Yuchan Li, Tian-wang Li, Lixiang Li, Jiaxi Li, Yalin Li, Jin-Liang Li, Pei-Zhi Li, Xiaoqiong Li, You Ran Li, Guanyu Li, Yixiao Li, Jinlan Li, Huizi Li, Jianping Li, Kathy H Li, Yun-Lin Li, Yadong Li, Sujing Li, Yuhua Li, Xuri Li, Wenzhuo Li, Y Li, Deqiang Li, Zipeng Li, Mingyue Li, Caixia Li, Hongli Li, Yun Li, Mengqiu Li, Ling-Ling Li, Yaqin Li, Yanfeng Li, Yu-He Li, Shasha Li, Xi Li, S-C Li, Siyi Li, Minmin Li, Manna Li, Chengwen Li, Dawei Li, Shu-Feng Li, Haojing Li, Xun Li, Ming-Jiang Li, Zhiyu Li, Sitao Li, Ziyang Li, Qian Li, Yaochen Li, Tinghua Li, Zhenfen Li, Wenyang Li, Bohao Li, Shuo Li, Wenming Li, Mingxuan Li, Si-Ying Li, Xinyi Li, Jenny J Li, Xue-zhi Li, Shuai Li, Anqi Li, Bingsong Li, Xiaonan Li, Xiaoju Li, Ting Li, Zhenyu Li, Xiang-Yu Li, Duan Li, Lei Li, Hongde Li, Fengqing Li, Na Li, Xunjia Li, Yanchang Li, Huibo Li, Ruixia Li, Nanzhen Li, Chuanfang Li, Bingjie Li, Hongxue Li, Pengsong Li, Ruotian Li, Xiaojing Li, Xinlin Li, Zong-Xue Li, En-Min Li, Chunya Li, Yan Ning Li, Honglin Li, Yu-Ying Li, Jinhua Li, Min-jun Li, Qian-Qian Li, Yuanheng Li, Chunxiao Li, Wenli Li, Shijun Li, Kuan Li, Mengze Li, Baoguang Li, Kaiwei Li, Jie-Shou Li, Zimeng Li, Mengmeng Li, W-B Li, Huangyuan Li, Lili Li, Binkui Li, Junxin Li, Yu-Sheng Li, Wei-Jun Li, Guoyan Li, Junjie Li, Fei-Lin Li, Nuomin Li, Shulin Li, Shanglai Li, Yanyan Li, Yue Li, Taibo Li, Junqin Li, Zhongcai Li, Xueying Li, Jun-Ru Li, JunBo Li, Zhaobing Li, Xiaoqi Li, Xiucui Li, Linxin Li, Haihua Li, Yu-Lin Li, Jen-Ming Li, Shujing Li, Tsai-Kun Li, Chen-Chen Li, Hongquan Li, Chuan F Li, Mengyun Li, Mingna Li, Yanxiang Li, Lanlan Li, Moyi Li, Xiyun Li, Yi-Wen Li, Shihong Li, Huifeng Li, Rulin Li, Ya-Pei Li, Lijuan Li, Shengbin Li, Yuanhong Li, Zhongjie Li, Zhenbei Li, Jingyu Li, Xuewei Li, Long Li, Shuangshuang Li, Wenjia Li, Min-Dian Li, Xiatian Li, Hongwei Li, Ding-Jian Li, Danni Li, Yangxue Li, Xiao-Qiang Li, Chengnan Li, Chuanyin Li, Min Li, Zhenzhou Li, Yiqiang Li, Pengyang Li, Kun-Xin Li, Xiawei Li, Binglan Li, Zesong Li, Yutong Li, Xiangpan Li, Mingfei Li, Shuwei Li, Yingnan Li, Ge Li, Mingdan Li, Xihe Li, Xinzhong Li, Jianfeng Li, Chenyao Li, Jun-Yan Li, Dexiong Li, Rongsong Li, Boru Li, Yinxiong Li, Ruixue Li, Zemin Li, Jixi Li, Chris Li, Jicheng Li, Hong-Yu Li, Chuanning Li, Weijian Li, Changhui Li, Jiafei Li, Yingying Li, Gaizhi Li, Chien-Hsiu Li, Xiangcheng Li, Siqi Li, Dechao Li, Chunxing Li, Wenxia Li, Guoxiang Li, Ziru Li, Qiao-Xin Li, Huang Li, Shu-Fang Li, Qiusheng Li, Man Li, Juxue Li, Weiqin Li, Xinming Li, Huayin Li, Xiao-yu Li, Jianyi Li, Yongjun Li, Mengyang Li, Guo-Jian Li, Guowei Li, Chenglong Li, Xingya Li, Nan Li, Gongda Li, Yajun Li, Wei-Ping Li, Yipeng Li, Mingxing Li, Nanjun Li, Xin-Yu Li, Chunyu Li, P H Li, Jinwei Li, Xuhua Li, Yu-Xiang Li, Ranran Li, Suping Li, Long Shan Li, Yanze Li, Jason Li, Xiao-Feng Li, Monica M Li, W Li, Fengjuan Li, Xianlun Li, Qi Li, Hainan Li, Yutian Li, Xiaoli Li, Xiliang Li, Shuangmei Li, Ying-Bo Li, Xionghui Li, Duanbin Li, Maogui Li, Dan Li, Sumei Li, Hongmei Li, Kang Li, Peilong Li, Yinghao Li, Xu-Wei Li, Mengsen Li, Lirong Li, Quanpeng Li, Wenhong Li, Audrey Li, Yijian Li, Yajiao Li, Guang Y Li, Xianyong Li, Qilan Li, Shilan Li, Qiuhong Li, Zongyun Li, Xiao-Yun Li, Guang-Li Li, Cheng-Lin Li, Bang-Yan Li, Enxiao Li, Jianrui Li, Yousheng Li, Guohua Li, Wen-Ting Li, Kezhen Li, Guoping Li, Xingxing Li, Ellen Li, A Li, Simin Li, Yijie Li, Weiguo Li, Xue-Nan Li, Xiaoying Li, Shengsheng Li, Suwei Li, Shuyu D Li, Jiandong Li, Ruiwen Li, Fangyong Li, Hong Li, Binru Li, Yuqi Li, Zihua Li, Yuchao Li, Hanlu Li, Xue-Peng Li, Jianang Li, Qing Li, Jiaping Li, Sheng-Tien Li, Yazhou Li, Shihao Li, Jun-Ling Li, Caesar Z Li, Feng Li, Weiyang Li, Peihong Li, Lang Li, Jin-Mei Li, Lisha Li, Feifei Li, Kejuan Li, Qinghong Li, Qiqiong Li, Cuicui Li, Xinxiu Li, Kaibo Li, Chongyi Li, Yi-Ying Li, Hanbing Li, Shaodan Li, Meng-Hua Li, Yongzheng Li, J T Li, Da-Hong Li, Xiao-mei Li, Jiejie Li, Ruihuan Li, Xiangwei Li, Baiqiang Li, Ziliang Li, Yaoyao Li, Mo Li, Yueguo Li, Donghe Li, Zheng Li, Ming-Hao Li, Congfa Li, Wenrui Li, Hongsen Li, Yong Li, Xiuling Li, Jingqi Li, Menghua Li, Ka Li, Kaixin Li, Fuping Li, Zhiyong Li, Jianbo Li, Xing-Wang Li, Chong Li, Xiao-Kang Li, Fugen Li, Hanqi Li, Yangyang Li, Yuwei Li, Dongfang Li, Xiaochen Li, Zhuorong Li, Zizhuo Li, X-H Li, Lan-Juan Li, Dong Sheng Li, Xianrui Li, Zhigao Li, Chenlin Li, Zihui Li, Xiaoxiao Li, Guoli Li, Le-Ying Li, Pengcui Li, Xiaoman Li, Huanqiu Li, Bing-Heng Li, Zhan Li, Weisong Li, Xinglong Li, Xiaohong Li, Xiaozhen Li, Yuan Hao Li, Jianchun Li, Wenxiang Li, Zhaoliang Li, Guo-Ping Li, Zhiyang Li, Cunxi Li, Zhifei Li, Jinhui Li, Ying Li, Jianlin Li, Yanshu Li, Yuanyou Li, Chongyang Li, Yumin Li, Wanyan Li, Longyu Li, Guiying Li, Jinku Li, X B Li, Zhisheng Li, Changgui Li, Cuiling Li, Xuekun Li, Yuguang Li, Wenke Li, Jiayi Li, Jianguo Li, En Li, Ximei Li, Shaoyong Li, Kai-Wen Li, Suwen Li, Peihua Li, Chang-Ping Li, Guangda Li, Yixue Li, Guandu Li, Junfeng Li, Xin-Chang Li, Jieming Li, Kongdong Li, Yue-Ying Li, Chunhui Li, Tongyao Li, Peiyu Li, Lian Li, Linfeng Li, Yuzhe Li, Xinmiao Li, Chenyang Li, Jiacheng Li, Chang-Yan Li, Qifang Li, Xiaohua Li, Vivian Li, Duanxiang Li, Xiaolin Li, Meiting Li, Justin Li, Xue-Er Li, Zhuangzhuang Li, Hongchang Li, Xiaohui Li, Cang Li, Xuepeng Li, Youwei Li, Mingjiang Li, Ronggui Li, Xingwang Li, Tiange Li, Yongjia Li, Dacheng Li, Xinmin Li, Zongyu Li, Luquan Li, Jianyong Li, Guoxing Li, Shujie Li, Zongchao Li, Yanbin Li, Jia Li, Shiliang Li, Haimin Li, Sheng-Qing Li, Qinrui Li, Yiming Li, Xiao-Tong Li, Lingjie Li, Yiwen Li, Tie Li, Baoqi Li, Wei-Bo Li, Leyao Li, Xiaoyi Li, Liyan Li, Xiao-Qin Li, Xinke Li, Xiaokun Li, Ming-Wei Li, Wenfeng Li, Minzhe Li, Jiajing Li, Karen Li, Yanlin Li, X Li, Liao-Yuan Li, Meifang Li, Yanjing Li, Yongkai Li, Maosheng Li, Ju-Rong Li, Jin Li, Shibo Li, Hangwen Li, Li-Na Li, Hengguo Li, An-Qi Li, Xuehua Li, Hui Li, AnHai Li, Chenli Li, Rumei Li, Zhengrui Li, Fangqi Li, Xiaoguang Li, Xian Li, Danjie Li, Yan-Yu Li, Vivian S W Li, Qinghua Li, Qinqin Li, Lipeng Li, Leilei Li, Defu Li, Ranchang Li, Lianyong Li, Amy Li, Zhou Li, Q Li, Haoyu Li, Xiaoyao Li, M-J Li, Jiao-Jiao Li, Zhu Li, Rongling Li, Tong-Ruei Li, Bizhi Li, Cheng-Wei Li, Wenwen Li, Guangqiang Li, Jian'an Li, Ben Li, Sichong Li, Wenyi Li, Yingxia Li, Meiyan Li, Qing-Min Li, Yonghe Li, Yun-Da Li, Xinwei Li, Shunhua Li, Yu-I Li, Mingxi Li, Jian-Qiang Li, Yingrui Li, Chenfeng Li, Qionghua Li, Guo-Li Li, Xingchen Li, Tianjiao Li, Ziqi Li, Shen Li, Gui-Rong Li, Shufen Li, Yunfeng Li, Yueqi Li, Yunpeng Li, Qiong Li, Xiao-Guang Li, Jiali Li, Zhencheng Li, Qiufeng Li, Songyu Li, Xu Li, Pinghua Li, Shi-Fang Li, Shude Li, Yaxiong Li, Zhibin Li, Zhenli Li, Qing-Fang Li, Rosa J W Li, Yunxiao Li, Hsin-Yun Li, Shengwen Li, Gui-Bo Li, XiaoQiu Li, Xueer Li, Zhi Li, Zhankui Li, Zihai Li, Yue-Jia Li, Haihong Li, Peifen Li, Taixu Li, Mingzhou Li, Jiejing Li, Meng-Miao Li, Meiying Li, Chunlian Li, Meng Li, Zhijie Li, Cun Li, Huimin Li, T Li, Ruifang Li, Xiao-xu Li, Man-Xiang Li, Yinghui Li, Cong Li, Chengbin Li, Feilong Li, Yuping Li, Sin-Lun Li, Mengfan Li, Weiling Li, Jie Li, Shiyan Li, Lianbing Li, G Li, Yanchun Li, Xuze Li, Zhi-Yong Li, Yukun Li, Wenjian Li, Jialin Li, He Li, Bichun Li, Xiong Bing Li, Hanqin Li, Qingjie Li, Wen Lan Li, Guoge Li, Han Li, Wen-Wen Li, Keying Li, Yutang Li, Minze Li, Xingcheng Li, Wanshun Li, Congxin Li, Hankun Li, Hongling Li, Xiangrui Li, Chaojie Li, Michelle Li, Caolong Li, Zhifan Li, J Li, Zhi-Jian Li, Jianwei Li, Yan-Guang Li, Jiexin Li, Hongyan Li, Ji-Min Li, Zhen-Xi Li, Guangdi Li, Peipei Li, Tian-Yi Li, Xiaxia Li, Yuefeng Li, Nien Li, Zhihao Li, Peiyuan Li, Yao Li, Zheyun Li, Tiansen Li, Chi-Yuan Li, Xiangfei Li, Xue Li, Zhonglin Li, Fen Li, Jieshou Li, Lin Li, Chenjie Li, Jinfang Li, Roger Li, Yanming Li, S L Li, Hong-Lan Li, Mengqing Li, Ben-Shang Li, Ming-Kai Li, Shunqing Li, Xionghao Li, Lan Li, Menglu Li, Huiqing Li, Yanwei Li, Yantao Li, Chien-Te Li, Wenyan Li, Xiaoheng Li, Zeyuan Li, Yongle Li, Ruolin Li, Hongqin Li, Zhenhao Li, Jonathan Z Li, Haying Li, Shao-Dan Li, Yong-Liang Li, Muzi Li, Gen Li, M Li, Dong-Ling Li, Chenwen Li, Jiehan Li, Yong-Jian Li, Le Li, Hongguo Li, Chenxin Li, Yongsen Li, Qingyun Li, Pengyu Li, Si-Wei Li, Ai-Qin Li, Zichao Li, Manru Li, Caili Li, Yingxi Li, Yuqian Li, Guannan Li, Wei-Dong Li, Cien Li, Qingyu Li, Xijing Li, Jingshang Li, Xingyuan Li, Dehua Li, Wenlong Li, Ya-Feng Li, Yanjiao Li, Jia-Huan Li, Yuna Li, Xudong Li, Guoxi Li, Xingfang Li, Shugang Li, Shengli Li, Jisheng Li, Rongyao Li, Xuan Li, Yongze Li, Ru Li, Yongxin Li, Lu Li, Jiangya Li, Yiche Li, Yilang Li, Zhuo-Rong Li, Qinglin Li, Bingbing Li, Runzhi Li, Yunshen Li, Jingchun Li, Qi-Jing Li, Hexin Li, Yanping Li, Zhenyan Li, H J Li, Ji Xia Li, Meizi Li, Yu-Ye Li, Qing-Wei Li, Qiang Li, Yuezheng Li, Hsiao-Hui Li, L I Li, Zhengnan Li, Jianglong Li, Hongzheng Li, Laiqing Li, Zhongxia Li, Ningyang Li, Guangquan Li, Xiaozheng Li, Shun Li, Hui-Jun Li, Guojun Li, Xuefei Li, Hung Li, Senlin Li, Jinping Li, Huili Li, Sainan Li, Jinghui Li, Zulong Li, Chengsi Li, P Li, Hongzhe K Li, Fulun Li, Xiao-Qiu Li, Jiejia Li, Yonghao Li, Mingli Li, Yehong Li, Zhihui Li, Yi-Yang Li, Fujun Li, Pei Li, Quanshun Li, Yongping Li, Liguo Li, Ni Li, Weimin Li, Mingxia Li, Xue-Hua Li, M V Li, Luxuan Li, Qiang-Ming Li, Yakui Li, Huafu Li, Xinye Li, Shichao Li, Gan Li, Chunliang Li, Ruiyang Li, Dapei Li, Zejian Li, Lihong Li, Chun Li, Jianan Li, Wenfang Li, Haixia Li, Sung-Chou Li, Xiangling Li, Lianhong Li, Jingmei Li, Ao Li, Yitong Li, Siwen Li, Yanlong Li, Cheng Li, Kui Li, Zhao Li, Tiegang Li, Yunxu Li, Zhong Li, Shuang-Ling Li, Xiao-Long Li, Hung-Yuan Li, Xiaofei Li, Xuanfei Li, Zilin Li, Zhang Li, Jianxin Li, Mingqiang Li, H Li, Xiaojiao Li, Dongliang Li, Chenxiao Li, Yinzhen Li, Hongjia Li, Xiao-Jing Li, Li-Min Li, Yunsheng Li, Xiangqi Li, Jian Li, Y H Li, Jia-Peng Li, Baichuan Li, Daoyuan Li, Haibo Li, Wenqi Li, Zhenzhe Li, Jian-Mei Li, Xiao-Jun Li, Kaimi Li, Yan-Hong Li, Peiran Li, Shi Li, Xueling Li, Qiao Li, Yi-Yun Li, Xiao-Cheng Li, Conghui Li, Xiaoxiong Li, Wanni Li, Yike Li, Yihan Li, Chitao Li, Haiyang Li, Junsheng Li, Jiayu Li, Xiaobai Li, Pingping Li, Mingquan Li, Wen-Ya Li, Rongxia Li, Suran Li, Yunlun Li, Yingqin Li, Yuanfang Li, Guoqin Li, Qiner Li, Huiqin Li, Shanhang Li, Jiafang Li, Chunlin Li, Han-Bing Li, Zongzhe Li, Yikang Li, Jisen Li, Si-Yuan Li, Caihong Li, Hongmin Li, Yajing Li, Peng Peng Li, Kenli Li, Guanglu Li, Benyi Li, Yuquan Li, Xiushi Li, Hongzhi Li, Dongmin Li, Jian-Jun Li, Fengyi Li, Yanling Li, Chengxin Li, Juanni Li, Xiaojiaoyang Li, C Li, Jian-Shuang Li, Xinxin Li, You-Mei Li, Chenglan Li, Dazhi Li, Yubin Li, Beixu Li, Yuhong Li, Fengqiao Li, Guiyuan Li, Di Li, Yanbing Li, Suk-Yee Li, Yuanyuan Li, Jufang Li, Shengjie Li, Xiaona Li, Shanyi Li, Hongbo Li, Chih-Chi Li, Xinhui Li, Zecai Li, Qipei Li, Xiaoning Li, Minghua Li, Jun Li, Xiyue Li, Zhuoran Li, Tianchang Li, Hongru Li, Shiqi Li, Mei-Ya Li, Wuyan Li, Mingzhe Li, Yi-Ling Li, Hongjuan Li, Yingjian Li, Zhirong Li, Wang Li, Mingyang Li, Weijun Li, Boyang Li, Senmao Li, Cai Li, Mingjie Li, Ling-Jie Li, Hong-Chun Li, Jingcheng Li, Ivan Li, Yaying Li, Mengshi Li, Liqun Li, Manxia Li, Ya Li, Changxian Li, Wen-Chao Li, Dan-Ni Li, Sunan Li, Zhencong Li, Chunqing Li, Jiong Li, Lai K Li, Yanni Li, Daiyue Li, Bingong Li, Huifang Li, Xiujuan Li, Yongsheng Li, Lingling Li, Chunxue Li, Yunlong Li, Xinhua Li, Jianshuang Li, Juanling Li, Minerva X Li, Xinbin Li, Alexander H Li, Xue-jing Li, Ding Li, Yuling Li, Wendeng Li, Xianlin Li, Yetian Li, Chuangpeng Li, Mingrui Li, Linyan Li, Yanjun Li, Shengze Li, Ming-Yang Li, Jiequn Li, Zhongding Li, Hewei Li, Da-Jin Li, Jiangui Li, Zhengyang Li, Cyril Li, Xinghui Li, Yuefei Li, Xiao-kun Li, Xinyan Li, Yuanhao Li, Xiaoyun Li, Congcong Li, Ji-Lin Li, Yushan Li, Ping'an Li, Juan Li, Huan Li, Weiping Li, Changjiang Li, Chengping Li, G-P Li, He-Zhen Li, Xiaobin Li, Shaoqi Li, Yuehua Li, Yinliang Li, Wen Li, Jinfeng Li, Shiheng Li, Weihai Li, Hsiao-Fen Li, Jiangan Li, Yu-Kun Li, Zhaojin Li, Bingxin Li, Mengjiao Li, Wenjuan Li, Wenyu Li, Meng-Meng Li, Chia-Yang Li, Tianxiang Li, Liangkui Li, Tian-chang Li, Hairong Li, Yahui Li, Su Li, Xi-Xi Li, Wenlei Li, Mei-Lan Li, Wenjun Li, Jiaxin Li, Haiyan Li, Ming D Li, Chenguang Li, Xujun Li, Ruyue Li, Chi-Ming Li, Xiaolian Li, Dandan Li, Yi-Ning Li, Yunan Li, Jiazhou Li, Zechuan Li, Zhijun Li, Sherly X Li, Ya-Ge Li, Wanling Li, Yinyan Li, Qijun Li, Rujia Li, Guangli Li, Lixia Li, Zhiwei Li, Xueshan Li, Yunrui Li, Yuhuang Li, Shanshan Li, Jiangbo Li, Wan-Shan Li, Xiaohan Li, Zhongwen Li, Huijie Li, W W Li, Yalan Li, Yiyang Li, Jing-gao Li, Xuejun Li, Fengxiang Li, Shunwang Li, Nana Li, Chao Li, Yaqing Li, Bingsheng Li, Yaqiao Li, Jingui Li, Huamao Li, Xiankun Li, Jingke Li, Xiaowei Li, Tianyao Li, Junming Li, Jianfang Li, Shubo Li, Qi-Fu Li, Zi-Zhan Li, Hai-Yun Li, Haoran Li, Zhongxian Li, Xiaoliang Li, Xinyuan Li, Maoquan Li, H-J Li, Zhixiong Li, Chumei Li, Shijie Li, Lingyan Li, Zhanquan Li, Wenguo Li, Fangyuan Li, Xuhang Li, Xiaochun Li, Chen-Lu Li, Xinjian Li, Jialun Li, Rui Li, Zilu Li, Xuemin Li, Zezhi Li, Sheng-Fu Li, Xue-Fei Li, Yudong Li, Shanpeng Li, Hongjiang Li, Wei-Na Li, Dong-Run Li, Yunxi Li, Jingyun Li, Binghua Li, Xuyi Li, Hanjun Li, Yunchu Li, Qihua Li, Zhengyao Li, Jin-Qiu Li, Jiaxuan Li, Jinghao Li, Y-Y Li, Xiaofang Li, Tuoping Li, Pengyun Li, Guangjin Li, Lin-Feng Li, Xutong Li, Ranwei Li, Kai Li, Ziqing Li, Keanning Li, Wei-Li Li, Yongjin Li, Shuangxiu Li, Chenhao Li, Ling Li, Weizu Li, Deming Li, Peiqin Li, Xiaodong Li, Nanxing Li, Qihang Li, Jianrong Li, Baoguo Li, Zhehui Li, Chenghao Li, Jiuyi Li, Chun-Xu Li, Luyao Li, Weike Li, Desheng Li, Zhixuan Li, Chuanbao Li, Long-Yan Li, Fuyu Li, Chuzhong Li, M D Li, Lingzhi Li, Yuan-Tao Li, Kening Li, Guilan Li, Wanshi Li, Ling-Zhi Li, Hengtong Li, Yifan Li, Ya-Li Li, Xiao-Sa Li, Songyun Li, Xiaoran Li, Bolun Li, Kunlin Li, Linchuan Li, Jiachen Li, Haibin Li, Shu-Qi Li, Zehua Li, Huangbao Li, Guo-Chun Li, Xinli Li, Mengyuan Li, S Li, Wenqing Li, Wenhua Li, Caiyun Li, Congye Li, Xinrui Li, Dehai Li, Wensheng Li, Jiannan Li, Qingshang Li, Guanbin Li, Zhiyi Li, Hanbin Li, Xing Li, Wanwan Li, Jia Li Li, Zhaoyong Li, SuYun Li, Shiyi Li, Wan-Hong Li, Suchun Li, Mingke Li, Xiaoyuan Li, Huanhuan Li, Yanan Li, Zongfang Li, Yang Li, Jiayan Li, YueQiang Li, Xiangping Li, H-H Li, Jinman Li, BoWen Li, Duoyun Li, Dongdong Li, Yimei Li, Hao Li, Liliang Li, Mengxi Li, Keyuan Li, Zhi-qiang Li, Shaojing Li, S S Li, Yi-Ting Li, Jiangxia Li, Yujie Li, Tong Li, Lihua Li, Yilong Li, Xue-Lian Li, Yan-Li Li, Zhiping Li, Haiming Li, Yansen Li, Gaijie Li, Yuemei Li, Jingfeng Li, Zhi-Yuan Li, Hai Li, Yanli Li, Kaibin Li, Yuan-Jing Li, Xuefeng Li, Wenjie Li, Xiaohu Li, Ruikai Li, Mengjuan Li, Xiao-Hong Li, Yinglin Li, Yaofu Li, Ren-Ke Li, Qiyong Li, Ruixi Li, Yi Li, Baosheng Li, Zhonglian Li, Yujun Li, Mian Li, Dalin Li, Lixi Li, Jin-Xiu Li, Kun Li, Qizhai Li, Jiwen Li, Pengju Li, Peifeng Li, Zhouhua Li, Ai-Jun Li, Qingqin S Li, Honglei Li, Guojin Li, Yueting Li, Xin-Yue Li, Dingchen Li, YaJie Li, Xiaoling Li, Jixuan Li, Yanqing Li, Zijian Li, Zhandong Li, Xuejie Li, Peining Li, Meng-Jun Li, Congjiao Li, Gaizhen Li, Huilin Li, Liang Li, Songtao Li, Fusheng Li, Huafang Li, Dai Li, Meiyue Li, Chenlu Li, Keshen Li, Kechun Li, Nianyu Li, Yuxin Li, X-L Li, Shaoliang Li, Shawn S C Li, Shu-Xin Li, Hong-Zheng Li, Tianye Li, Cuiguang Li, Dongye Li, Qun Li, Zhen Li, Yuan Li, Chunhong Li, F Li, Mengling Li, Kunpeng Li, Jia-Da Li, Zhenghao Li, Chun-Bo Li, Zhantao Li, Baoqing Li, Pu Li, Xinle Li, Xingli Li, Bingkun Li, Nien-Chi Li, Wuguo Li, Tiewei Li, Bing-Hui Li, Rong-Bing Li, Daniel Tian Li, Jingyong Li, Honggang Li, Shikang Li, Rong Li, Wei-Yang Li, Mingkun Li, Binxing Li, Shi-Ying Li, Zixiao Li, Ming Xing Li, Guixin Li, Quanzhang Li, Ming-Xing Li, Marilyn Li, Da-wei Li, Shishi Li, Hong-Lian Li, Bei-Bei Li, Haitong Li, Xiumei Li, Melody M H Li, Ruibing Li, Yuli Li, Qingfang Li, Peibo Li, Qibing Li, Huanjun Li, Heng Li, Wende Li, Chung-Hao Li, Liuzheng Li, Zhanjun Li, Yifei Li, Tianming Li, Chang-Sheng Li, Xiao-Na Li, Tianyou Li, Jipeng Li, Xidan Li, Yixing Li, Chengcheng Li, Yu-Jin Li, Baoting Li, Longxuan Li, Ka Wan Li, Huiyou Li, Shi-Guang Li, Wenxiu Li, Binbin Li, Xinyao Li, Zhuang Li, Gui-xing Li, Yu-Hao Li, Shunle Li, Niu Li, Shilin Li, Siyue Li, Diyan Li, Mengyao Li, Shili Li, Yixuan Li, Shan-Shan Li, Zhuanjian Li, Meiqing Li, Gerard Li, Yuyun Li, Hengyu Li, Zhiqiong Li, Zonglin Li, Yinhao Li, Pik Yi Li, Junying Li, Jingxin Li, Mufan Li, Chun-Lai Li, Defeng Li, Shiya Li, Zu-guo Li, Xin-Zhu Li, Xiao-Jiao Li, Jia-Xin Li, Kuiliang Li, Pindong Li, Hualian Li, Youchen Li, Junhong Li, Li Li, W Y Li, Hanxue Li, Lulu Li, Yi-Heng Li, Xiaoqin Li, L P Li, Runbing Li, Chunmei Li, Mingjun Li, Yuanhua Li, Qiaolian Li, Yanmin Li, Ji-Cheng Li, Jingyi Li, Yuxiang Li, Haolong Li, Hao-Fei Li, Xuanzheng Li, Peng-li Li, Quan Li, Yining Li, Xue-Ying Li, Xiurong Li, Huijuan Li, Haiyu Li, Xu-Zhao Li, Yunze Li, Yanzhong Li, Guohui Li, Kainan Li, Yongzhe Li, Qingfeng Li, Tianyi Li, Xiaoyan Li, Nanlong Li, Ping Li, Xu-Bo Li, Nien-Chen Li, Fangzhou Li, Yue-Chun Li, Jiahui Li, Huiping Li, Kangyuan Li, Biao Li, Yuanchuang Li, Haiying Li, Yunting Li, Xiaoxuan Li, Anyao Li, Hongliang Li, Qing-Chang Li, Hong-Yan Li, Shengbiao Li, Yue-Rui Li, Ruidong Li, Dalei Li, Zongjun Li, Y M Li, Changqing Li, Hanting Li, Dong-Jie Li, Xiaomin Li, Sijie Li, Dengxiong Li, Meilan Li, D C Li, Andrew C Li, Jianye Li, Yi-Shuan J Li, Tinghao Li, Zhouxiang Li, Qiuyan Li, Tingguang Li, Yun-tian Li, Jianliang Li, Xiangyang Li, Guangzhao Li, Yixi Li, Chunjie Li, Shuyu Dan Li, S A Li, Tianfeng Li, Anna Fen-Yau Li, Minghui Li, Jiangfeng Li, Jinjie Li, Liming Li, Jie-Pin Li, Junyi Li, Kaiyi Li, Wenqun Li, Dongtao Li, Fengyuan Li, Guixia Li, Yinan Li, Aoxi Li, Zuo-Lin Li, Chenxi Li, Yuanjing Li, Zhengwei Li, Linqi Li, Bingjue Li, Xixi Li, Yan-Chun Li, Binghu Li, Suiyan Li, Yu-Hang Li, Qiaoqiao Li, Xiaotian Li, Zhenguang Li, Shuhui Li, Jia-Ru Li, Shu-Hong Li, Pei-Qin Li, Chun-Xiao Li, Shuyue Li, Mengying Li, Fangyan Li, Tongzheng Li, Quan-Zhong Li, Yihong Li, Yaxian Li, Duo Li, Dali Li, Zhiming Li, Xuemei Li, Hongxia Li, Xueting Li, Yongting Li, Danyang Li, Zhenjun Li, Ren Li, Tiandong Li, Lanfang Li, Hongye Li, Di-Jie Li, Mingwei Li, Bo Li, Jinliang Li, Wenxin Li, Qiji Li, W J Li, Zhipeng Li, Zhijia Li, Xiaoping Li, Jingtong Li, Linhong Li, Taoyingnan Li, Lucy Li, Lieyou Li, Zhengpeng Li, Xiayu Li, Huabin Li, Mao Li, Baolin Li, Cuilan Li, Yuting Li, Yongchao Li, Xiaobo Li, Xiaoting Li, Ruotai Li, Meijia Li, Shujiao Li, Yaojia Li, Weirong Li, Xiao-Yao Li, Kun-Ping Li, Weihua Li, Shangming Li, Yibo Li, Yaqi Li, Gui-Hua Li, Zhihong Li, Runzhao Li, Yandong Li, Chaowei Li, Xiang-Dong Li, Huiyuan Li, Yuchun Li, Yingjun Li, Xiufeng Li, Yanxin Li, Xiaohuan Li, Ying-Qin Li, Boya Li, Lamei Li, O Li, Fan Li, Suheng Li, Joyce Li, Jun Z Li, Yiheng Li, Taiwen Li, Hui-Ping Li, Xiaorong Li, Zhiqiang Li, Junru Li, Hecheng Li, Jiangchao Li, Haifeng Li, Changkai Li, Yueping Li, Liping Li, Rena Li, Jiangtao Li, Yu-Jui Li, Zhenglong Li, Yajuan Li, Xuanxuan Li, Rui-Jún Eveline Li, Bing-Mei Li, Yunman Li, Chaoqian Li, Shuhua Li, Yu-Cheng Li, Chunying Li, Yirun Li, Haomiao Li, Weiheng Li, Leipeng Li, Qianqian Li, Baizhou Li, Zhengliang Li, YiQing Li, Han-Ru Li, Weijie Li, Sheng Li, Wei-Qin Li, Guoyin Li, Yaqiang Li, Qingxian Li, Zongyi Li, Dan-Dan Li, Yeshan Li, Qiwei Li, Zirui Li, Yongpeng Li, Chengjun Li, Keke Li, Jianbin Li, Chanyuan Li, Shiying Li, Jianxiong Li, Huaying Li, Ji Li, Tuojian Li, Yixin Li, Ziyue Li, Juntong Li, Zhongzhe Li, Xiang Li, Yumei Li, Xiang-Ping Li, Chaonan Li, Wenqiang Li, Yu-Chia Li, Pei-Shan Li, Zaibo Li, Shaomin Li, Heying Li, Guangming Li, Xuan-Ling Li, Yuxuan Li, Bingshan Li, Xiaoqiang Li, Jiahao Li, Hanxiao Li, Jiansheng Li, Shuying Li, Shibao Li, Xiaomei Li, Ruijin Li, Kunlong Li, Pengjie Li
articles
Lan Zhou, Xin Li, Zihan Ji +9 more · 2025 · Molecular biotechnology · Springer · added 2026-04-24
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disease. Genetic linkage analyses have identified that mutations in the exostosin glycosyltransferase (EXT)1 and EXT2 genes are li Show more
Hereditary multiple exostoses (HME) is an autosomal dominant skeletal disease. Genetic linkage analyses have identified that mutations in the exostosin glycosyltransferase (EXT)1 and EXT2 genes are linked to HME pathogenesis, with EXT1 mutation being the most frequent. The aim of this study was to generate a mice model with Ext1 gene editing to simulate human EXT1 mutation and investigate the genetic pathogenicity of Ext1 through phenotypic analyses. We designed a pair of dual sgRNAs targeting exon 1 of the mice Ext1 gene for precise deletion of a 46 bp DNA fragment, resulting in frameshift mutation of the Ext1 gene. The designed dual sgRNAs and Cas9 proteins were injected into mice zygotes cytoplasm. A total of 14 mice were obtained via embryo transfer, among which two genotypic chimera mice had a deletion of the 46 bp DNA fragment in exon 1 of the Ext1 gene. By hybridization and breeding, we successfully generated heterozygous mice with edited Ext1 gene (Ext Show less
📄 PDF DOI: 10.1007/s12033-024-01325-0
EXT1
Fawang Du, Hanchao Wang, Zhihong Chen +7 more · 2025 · Journal of asthma and allergy · added 2026-04-24
Asthma severity assessment is essential for asthma management. Transcriptomics contributes substantially to asthma pathogenesis. Then, this study aimed to explore asthma severity-associated transcript Show more
Asthma severity assessment is essential for asthma management. Transcriptomics contributes substantially to asthma pathogenesis. Then, this study aimed to explore asthma severity-associated transcriptomics profile and promising biomarkers for asthma severity prediction. In discovery cohort, induced sputum cells from 3 non-severe and 3 severe asthma patients were collected and analyzed using RNA-seq. Multivariate analysis was performed to explore asthma severity-associated transcriptomics profile and differential expressed genes (DEGs). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used for pathway enrichment analysis. Subsequently, based on the previous study and clinical experience, the mRNA expressions of 6 overlapped asthma severity-associated DEGs and Distinct asthma severity-associated transcriptomics profile was identified in induced sputum cells in discovery cohort. Then, 345 DEGs were found, of which 38 terms and 32 pathways were enriched using GO and KEGG, respectively. In validation cohort, the mRNA expressions of Collectively, this study provides the first identification of the association between induced sputum cells transcriptomics profile and asthma severity, indicating the potential value of transcriptomics for asthma management. The study also reveals the promising value of serum C3 for predicting asthma severity in clinical practice. Show less
no PDF DOI: 10.2147/JAA.S517140
NRXN3
Linjie Ma, Yuqiu Zhou, Chao Li +2 more · 2025 · Annals of medicine · Taylor & Francis · added 2026-04-24
To explore the influence related factors of endoscopic assistant in gasless transaxillary endoscopic thyroidectomy by using machine learning and nomogram, and construct an endoscopic assistant system. Show more
To explore the influence related factors of endoscopic assistant in gasless transaxillary endoscopic thyroidectomy by using machine learning and nomogram, and construct an endoscopic assistant system. A skilled endoscopic assistant(Group A, The learning curve coefficient of goodness of fit R It is necessary to train endoscopic assistant to build an endoscopic assistant system, and improve the surgical process by shortening CET, TRT and reduce LWT times. The importance of experience accumulation to improve the efficiency of surgery should be emphasized. Show less
📄 PDF DOI: 10.1080/07853890.2025.2537354
CETP
Guofeng Xing, Li Chen, Lizhi Lv +5 more · 2025 · Journal of cardiovascular development and disease · MDPI · added 2026-04-24
This study examines pediatric cardiomyopathies by analyzing genetic and clinical data from 55 patients (2021-2024) at Beijing Anzhen Hospital. Four subtypes were studied: dilated (DCM, 24), hypertroph Show more
This study examines pediatric cardiomyopathies by analyzing genetic and clinical data from 55 patients (2021-2024) at Beijing Anzhen Hospital. Four subtypes were studied: dilated (DCM, 24), hypertrophic (HCM, 22), arrhythmogenic right ventricular (ARVC, 7), and restrictive (RCM, 2). Clinical data, imaging, labs, and family histories were collected, with whole-exome sequencing (WES) identifying disease-causing variants classified via ACMG guidelines. Statistical analysis revealed a median age of 11 years, a proportion of 58% male participants, and ethnic diversity (21 northern Han, 29 southern Han, 5 minorities). In the cohort, 13 cases had an LVEF below 35%. Pathogenic/likely pathogenic (P/LP) variants were found in 21.8% of the patients, and variants of uncertain significance (VUS) were present in 38.2%, with Show less
📄 PDF DOI: 10.3390/jcdd12120466
MYBPC3
Wei Xu, Mingjie Li, Xiang Ma +3 more · 2025 · BMC public health · BioMed Central · added 2026-04-24
The relationship between ambient air pollution and chronic liver disease (CLD), and whether physical activity (PA) modifies this association, remains unclear. We analyzed 17,708 middle-aged and older Show more
The relationship between ambient air pollution and chronic liver disease (CLD), and whether physical activity (PA) modifies this association, remains unclear. We analyzed 17,708 middle-aged and older adults from the 2013 China Health and Retirement Longitudinal Study (CHARLS). Individual-level exposures to CO, O In fully adjusted models, higher pollutant levels were associated with increased CLD risk: CO (OR 1.13, 95% CI 1.04-1.19, p = 0.025), O Ambient CO, O Show less
📄 PDF DOI: 10.1186/s12889-025-25378-1
LPA
Zheyi Wang, Yize Sun, Zetai Bai +3 more · 2025 · Movement disorders : official journal of the Movement Disorder Society · Wiley · added 2026-04-24
Mitochondrial dysfunction is increasingly recognized as a key factor in neurodegenerative diseases (NDDs), underscoring the therapeutic potential of targeting mitochondria-related genes. This study ai Show more
Mitochondrial dysfunction is increasingly recognized as a key factor in neurodegenerative diseases (NDDs), underscoring the therapeutic potential of targeting mitochondria-related genes. This study aimed to identify novel biomarkers and drug targets for these diseases through a comprehensive analysis that integrated genome-wide Mendelian randomization (MR) with genes associated with mitochondrial function. Using existing publicly available genome-wide association studies (GWAS) summary statistics and comprehensive data on 1136 mitochondria-related genes, we initially identified a subset of genes related to mitochondrial function that exhibited significant associations with NDDs. We then conducted colocalization and summary-data-based Mendelian randomization (SMR) analyses using expression quantitative trait loci (eQTL) to validate the causal role of these candidate genes. Additionally, we assessed the druggability of the encoded proteins to prioritize potential therapeutic targets for further exploration. Genetically predicted levels of 10 genes were found to be significantly associated with the risk of NDDs. Elevated DMPK and LACTB2 levels were associated with increased Alzheimer's disease risk. Higher expression of NDUFAF2, BCKDK, and MALSU1, along with lower TTC19, raised Parkinson's disease risk. Higher ACLY levels were associated with both amyotrophic lateral sclerosis and multiple sclerosis (MS) risks, while decreased MCL1, TOP3A, and VWA8 levels raised MS risk. These genes primarily impact mitochondrial function and energy metabolism. Notably, several druggable protein targets identified are being explored for potential NDDs treatment. This data-driven MR study demonstrated the causal role of mitochondrial dysfunction in NDDs. Additionally, this study identified candidate genes that could serve as potential pharmacological targets for the prevention and treatment of NDDs. © 2025 International Parkinson and Movement Disorder Society. Show less
no PDF DOI: 10.1002/mds.30123
BCKDK
Fokhrul Hossain, Martha I Gonzalez-Ramirez, Jone Garai +13 more · 2025 · International journal of molecular sciences · MDPI · added 2026-04-24
Triple-negative breast cancer (TNBC) is an aggressive, heterogeneous subtype of breast cancer. miRNAs play an essential role in TNBC pathogenesis and prognosis. Obesity is linked with an increased ris Show more
Triple-negative breast cancer (TNBC) is an aggressive, heterogeneous subtype of breast cancer. miRNAs play an essential role in TNBC pathogenesis and prognosis. Obesity is linked with an increased risk for several cancers, including breast cancer. Obesity is also related to the dysregulation of miRNA expression in adipose tissues. However, there is limited knowledge about race- and obesity-specific differential miRNA expression in TNBC. We performed miRNA sequencing of 48 samples (24 tumor and 24 adjacent non-tumor tissues) and RNA sequencing of 24 tumors samples from Black (AA) and White (EA) TNBC patients with or without obesity. We identified 55 miRNAs exclusively associated with tumors in obese EA patients and 33 miRNAs in obese AA patients, each capable of distinguishing tumor tissues from obese from lean individuals within their respective racial groups. In EA, we detected 41 significant miRNA-mRNA correlations. Notably, miR-181b-5p and miR-877-5p acted as negative regulators of tumor-suppressor genes (e.g., Show less
📄 PDF DOI: 10.3390/ijms26189101
HEY2
Jing Li, Zan Song, Xue Dong +12 more · 2025 · Cell death & disease · Nature · added 2026-04-24
Vaccinia-related kinase 1 (VRK1) is involved in numerous cellular processes, including DNA repair, cell cycle and cell proliferation. However, its roles and molecular mechanism underlying the progress Show more
Vaccinia-related kinase 1 (VRK1) is involved in numerous cellular processes, including DNA repair, cell cycle and cell proliferation. However, its roles and molecular mechanism underlying the progression of hepatocellular carcinoma (HCC) are yet largely unexplored. Here, we demonstrated that VRK1 expression is elevated in HCC tumor tissues, which is associated with high tumor stage and poor prognosis in HCC patients. In vitro and in vivo experiments manifested that VRK1 overexpression significantly promotes cell proliferation, colony formation, migration and tumor growth of HCC by inducing epithelial-mesenchymal transition (EMT) program. Mechanistically, immunoprecipitation combined with mass spectrometry analysis determined that VRK1 interacts with CHD1L, which mediates the phosphorylation of CHD1L at serine 122 site. RNA-seq revealed that one of the key downstream target genes of VRK1 is SNAI1, by which VRK1 promotes EMT process and HCC progression. Furthermore, VRK1 upregulates SNAI1 expression through phosphorylating CHD1L. In conclusion, these findings suggested that VRK1/CHD1L/SNAI1 axis acts as a cancer-driving pathway to promote the proliferation and EMT of HCC, indicating that targeting VRK1 may be an attractive therapeutic strategy of HCC. Show less
no PDF DOI: 10.1038/s41419-025-07641-w
SNAI1
Jiangwei Qin, Yunfan Zhang, Ruolan Hu +4 more · 2025 · Italian journal of pediatrics · BioMed Central · added 2026-04-24
Neurodevelopmental disorders such as attention deficit and disruptive behaviour disorders (ADHD), autism spectrum disorder (ASD), and schizophrenia have been increasingly prevalent recently. Previous Show more
Neurodevelopmental disorders such as attention deficit and disruptive behaviour disorders (ADHD), autism spectrum disorder (ASD), and schizophrenia have been increasingly prevalent recently. Previous research has demonstrated that inflammatory activity from autoimmune diseases is involved in neurological diseases. However, some studies question the association between inflammatory activities and neurodevelopmental disorders. Herein, we attempt to clarify this relationship using Mendelian randomization (MR) analysis. We used systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and type 1 diabetes mellitus (T1D) to represent autoimmune diseases. First, we conducted MR analysis to examine associated SNPs between autoimmune and neurodevelopmental disorders. Second, we performed bidirectional MR analysis to identify 429 types of signalling peptides and proteins or relevant receptors with causality reported diseases. Finally, we compared the genes with the gene loci identified in the available TWAS-hub site. The MR results of autoimmune diseases on neurodevelopmental disorders did not present any significant association in all models. However, we identified 20-45 factors in ADHD, ASD, and schizophrenia, including semaphorin 3, IL-27 receptor subunit alpha, and fibroblast growth factor 16, which were considered clinically significant pro-inflammatory mediators. GO and KEGG enrichment analyses revealed unequal integrities among the three neurodevelopmental diseases, and we failed to identify a shared pathway linking autoimmune diseases and neurodevelopmental disorders. TWAS analysis indicated that CHRNA5 potentially mediates inflammatory activities in schizophrenia. According to our data, we failed to identify an association between autoimmune diseases and neurodevelopmental disorders. However, we demonstrated that some pro-inflammatory factors are involved in neurodevelopmental disorders. Show less
📄 PDF DOI: 10.1186/s13052-025-01910-2
IL27
Xiaojing Liu, Suxia Wang, Gang Liu +7 more · 2025 · Theranostics · added 2026-04-24
📄 PDF DOI: 10.7150/thno.101498
ANGPTL4
Zhuo Liu, Dandan Zhao, Baoming Wang +14 more · 2025 · The oncologist · Oxford University Press · added 2026-04-24
Despite the increasing approval and ongoing clinical trials of FGFR-targeted therapies, accurately detecting FGFR fusions remains a challenge due to limited research, low incidence rates, complex fusi Show more
Despite the increasing approval and ongoing clinical trials of FGFR-targeted therapies, accurately detecting FGFR fusions remains a challenge due to limited research, low incidence rates, complex fusion partner distribution, and unique kinase domain distribution. We conducted a multicenter study to comprehensively profile FGFR fusions in the largest Chinese pan-cancer cohort to date, comprising 118 FGFR fusions from 114 individuals. Both DNA- and RNA-based sequencing approaches were utilized to reveal novel and fundamental features of FGFR fusion. Our research reveals an incidence rate of 0.96% for FGFR rearrangements within this Chinese cohort, including a high incidence rate of FGFR fusions (40%) in parotid gland carcinoma. However, this is based on a small sample size of 5 tumors and should be interpreted cautiously pending validation in larger cohorts. We also uncovered distinct breakpoint distribution patterns across various FGFR rearrangements. For example, a primary breakpoint in intron17 of FGFR2 was predominant (21/22), while FGFR1/3 breakpoints displayed substantial diversity. For the first time, we identified "hot" breakpoints in FGFR1 intron17, exon18, and FGFR3's 3' untranslated region. These findings underline the importance of incorporating these regions in targeted sequencing to ensure comprehensive detection of FGFR1/3 fusions. Notably, we observed a predilection for intrachromosomal distribution in common FGFR1/2/3 fusions. In contrast, most novel fusions (12/15) exhibited an interchromosomal distribution pattern, indicating variations in the fusion formation mechanism. Importantly, our study demonstrates the substantial incremental value of RNA-NGS or other orthogonal methods in confirming the functionality of FGFR rearrangements initially identified by DNA sequencing. In our cohort, 46% (6/13) of rare FGFR1/2/3 fusions lacked detectable RNA transcripts; however, this does not definitively indicate non-functionality as factors such as low RNA quality, expression below detection limits, or nonsense-mediated decay may contribute. Therefore, RNA-based validation is critical for accurately identifying potentially targetable FGFR fusions and guiding therapy. Our findings offer critical novel insights into functional FGFR fusions and bear considerable clinical implications for identifying individuals whose tumors are most likely to respond favorably to FGFR-targeted therapies. Show less
📄 PDF DOI: 10.1093/oncolo/oyaf347
FGFR1
Zhengdong Wei, Shasha Zhang, Keke Bai +11 more · 2025 · Development (Cambridge, England) · added 2026-04-24
Twenty types of GABAergic interneurons form intricate networks to fine-tune neural circuits in the brain. Parvalbumin-positive (PV+) and somatostatin-positive (SST+) interneurons, which are the two la Show more
Twenty types of GABAergic interneurons form intricate networks to fine-tune neural circuits in the brain. Parvalbumin-positive (PV+) and somatostatin-positive (SST+) interneurons, which are the two largest populations of neocortical interneurons, innervate the soma and/or proximal dendrites, and distal dendrites of pyramidal neurons, respectively. Using PV- and SST-specific knockout mouse models, we show that PV+ interneurons require FGFR2, which responds to FGF7, to drive PV+ inhibitory presynaptic maturation on perisomatic regions of Layer V pyramidal neurons. In contrast, SST+ interneurons rely on both FGFR1 and FGFR2, which respond to FGF10 or FGF22, to promote SST+ inhibitory presynaptic maturation on distal dendrites of pyramidal neurons in cortical Layer I. Mechanistically, FGF-FGFR signaling sustains VGAT protein levels in interneurons through PP2A and Akt pathways. Together, these findings demonstrate that distinct FGF ligand-receptor combinations regulate inhibitory presynaptic differentiation by PV+ and SST+ interneurons, contributing to the formation of compartment-specific synaptic patterns. Show less
no PDF DOI: 10.1242/dev.204532
FGFR1
Mimi Li, Lichao Ye, Chunnuan Chen · 2025 · Scientific reports · Nature · added 2026-04-24
Despite the well-established association between the apolipoprotein B/apolipoprotein A1 (apoB/apoA1) ratio and ischemic stroke, its specific relationship with the underlying vascular pathologies contr Show more
Despite the well-established association between the apolipoprotein B/apolipoprotein A1 (apoB/apoA1) ratio and ischemic stroke, its specific relationship with the underlying vascular pathologies contributing to stroke remains poorly understood. This study aims to investigate the association between the apoB/apoA1 ratio and intracranial or extracranial atherosclerosis. We enrolled 408 patients with acute ischemic stroke who had never been treated with statins or fibrates. Based on the images from computed tomography angiography (CTA), the patients were categorized into four groups: intracranial atherosclerosis stenosis (ICAS, n = 136), extracranial carotid atherosclerosis stenosis (ECAS, n = 45), combined intracranial and extracranial atherosclerosis stenosis (COAS, n = 73), and non-cerebral atherosclerosis stenosis (NCAS, n = 154). Demographic characteristics, clinical factors, and serum lipid levels were collected and then compared across groups. The apoB/apoA1 ratio was significantly higher in patients with ICAS, ECAS and COAS compared to those in the NCAS group. Multivariable logistic regression analysis demonstrated that the ApoB/ApoA1 ratio was independently associated with ICAS, but not with ECAS. ROC curve analysis showed that the ApoB/ApoA1 ratio had a good diagnostic ability for ICAS, with an area under the curve (AUC) of 0.764, an optimal cut-off value of 0.8122, a sensitivity of 81.3%, and a specificity of 59.8%. An higher apoB/apoA1 ratio is associated with ICAS in ischemic stroke patients. Show less
📄 PDF DOI: 10.1038/s41598-025-97625-9
APOB
Zhiyang Li, Xuelian Li, Rui Shen +7 more · 2025 · Biomolecules · MDPI · added 2026-04-24
As a novel member of the interleukin(IL)-1 family, IL-38 has shown therapeutic effects in various chronic inflammatory diseases. However, its role and underlying mechanisms in cardiovascular diseases, Show more
As a novel member of the interleukin(IL)-1 family, IL-38 has shown therapeutic effects in various chronic inflammatory diseases. However, its role and underlying mechanisms in cardiovascular diseases, particularly atherosclerosis, remain unclear. This study aimed to explore the effects of IL-38 on atherosclerosis progression and its mechanisms in regulating macrophage function during the atherosclerotic process. To evaluate the therapeutic potential of IL-38 in atherosclerosis, we performed histopathological examinations and biochemical analyses in vivo. In vitro, we used primary bone marrow-derived macrophages (BMDMs) stimulated with oxidized low-density lipoprotein (ox-LDL) to assess the anti-inflammatory effects of IL-38 and quantified its impact on ox-LDL-induced macrophage polarization. To further elucidate the specific mechanisms by which IL-38 regulates macrophage function, we conducted mRNA sequencing and validated downstream regulatory signaling pathways. IL-38 exhibited therapeutic potential in atherosclerosis by reducing atherosclerotic plaque formation, modulating plaque composition, suppressing the production of proinflammatory cytokines within plaques, and potentially regulating macrophage cholesterol metabolism. Moreover, IL-38 exerted significant anti-inflammatory effects on macrophages both in vivo and in vitro. Notably, it inhibited the polarization of macrophages toward the proinflammatory M1-like phenotype in both settings. Additionally, IL-38 impeded the phosphorylation and nuclear translocation of p65 in BMDMs and reduced ox-LDL-induced macrophage apoptosis. IL-38 holds therapeutic potential for atherosclerosis, as it alleviates disease progression, inhibits macrophage polarization toward the M1-like phenotype, suppresses nuclear factor-κB (NF-κB) signaling activation, and reduces macrophage apoptosis. This study provides new insights into the anti-inflammatory mechanisms by which IL-38 mitigates atherosclerosis. Show less
📄 PDF DOI: 10.3390/biom15121741
APOE
Qinze Yu, Chang Zhou, Jiyue Jiang +2 more · 2025 · Bioinformatics (Oxford, England) · Oxford University Press · added 2026-04-24
Accurate and generalizable prediction of drug-target interactions (DTIs) remains a critical challenge for drug discovery, particularly when addressing underexplored targets and compounds. Recent advan Show more
Accurate and generalizable prediction of drug-target interactions (DTIs) remains a critical challenge for drug discovery, particularly when addressing underexplored targets and compounds. Recent advances in graph neural networks and large-scale pre-trained models offer new opportunities to capture rich structural and functional features essential for DTI prediction while enhancing the generalization ability. We present GS-DTI, a graph structure-based DTI prediction framework that integrates molecular graph transformers, protein language models, and protein tertiary structure. Our method achieved robust and interpretable DTI predictions. GS-DTI extracts drug features from SMILES-derived molecular graphs using a knowledge-guided pre-trained transformer, while protein features are derived from both sequence and predicted 3D structure for comprehensive representation. A multi-task loss function equipped with contrastive learning is adopted to enhance generalization and functional interpretability. Extensive experiments on the benchmarks and challenging cross-domain settings demonstrate that GS-DTI achieves state-of-the-art performance. Notably, our model improves the MCC by over 10% compared to previous methods in the drug-target pair cold start test. The model can pinpoint the binding pockets of the targets, offering robust interpretability, and case studies show GS-DTI's promising potential in virtual screening for new candidate drugs of BACE1. The GS-DTI source code and processed datasets are available at https://github.com/purvavideha/GSDTI. All experimental data are derived from public sources. Show less
📄 PDF DOI: 10.1093/bioinformatics/btaf445
BACE1
Yuanyuan Li, Qiaolin Yu, Rong Yao +11 more · 2025 · Patient preference and adherence · added 2026-04-24
The treatment of multidrug-resistant tuberculosis (MDR-TB) is characterized by a prolonged duration and complex medication regimens, often resulting in a substantial medication-related burden that neg Show more
The treatment of multidrug-resistant tuberculosis (MDR-TB) is characterized by a prolonged duration and complex medication regimens, often resulting in a substantial medication-related burden that negatively impacts patients' adherence and quality of life. However, research on the heterogeneity of medication-related burden among MDR-TB patients and its influencing factors remains limited. This study aimed to identify latent profiles of medication-related burden among MDR-TB patients and examine differences in burden characteristics across these profiles, thereby providing evidence for tailored intervention strategies. A convenience sampling method was employed to recruit MDR-TB patients diagnosed at a tertiary infectious disease hospital in Chengdu between December 2024 and May 2025. Data were collected using a general information questionnaire, the Living with Medicines Questionnaire (LMQ), and the Health Literacy Management Scale (HeLMS). Latent profile analysis (LPA) was conducted to identify distinct profiles of medication-related burden, and multivariate logistic regression was used to explore associated factors for each profile. A total of 214 valid responses were analyzed. The LPA identified two distinct profiles of medication-related burden: C1 - "Low-Burden (Attitude & Practice-Dominated)" (44%) and C2 - "High-Burden (Daily Interference-Dominated)" (56%). Absence of side effects, not employing a caregiver, and higher levels of health literacy were positively associated with membership in the C1 group ( Medication-related burden among MDR-TB patients exhibits clear heterogeneity. Healthcare professionals should adopt stratified management and personalized interventions based on the identified influencing factors to alleviate the burden of medication in this population. Show less
📄 PDF DOI: 10.2147/PPA.S558068
LPA
Ruibing Li, Jinyang Wang, Jianan Wang +7 more · 2025 · Journal of inflammation research · added 2026-04-24
Neuromyelitis optica spectrum disorder (NMOSD) is a group of immune-mediated disorders that often lead to severe disability. The diagnosis and monitoring of NMOSD can be challenging, particularly in s Show more
Neuromyelitis optica spectrum disorder (NMOSD) is a group of immune-mediated disorders that often lead to severe disability. The diagnosis and monitoring of NMOSD can be challenging, particularly in seronegative cases, highlighting the need for reliable biomarkers to enhance clinical management. This study aimed to identify serum lipid biomarkers for the diagnosis and monitoring of NMOSD and to assess their potential to improve clinical decision-making. We conducted a comprehensive serum proteomic analysis in a discovery cohort of NMOSD patients and controls to identify lipid-related proteins associated with NMOSD. Subsequently, we validated the candidate biomarkers in the retrospective cohort and developed diagnostic models using a random forest algorithm. The association between these lipid biomarkers and disease activity was further evaluated in longitudinal analysis. Our analysis identified a panel of serum lipid-related biomarkers that demonstrated significant differences between NMOSD patients and controls. The diagnostic models achieved the impressive accuracy of 72% for the full NMOSD spectrum, 72% for AQP4-IgG+ NMOSD, and 68% for double seronegative NMOSD. Importantly, these biomarkers showed a correlation with disease activity, with levels changing from relapse to remission. Additionally, a combination of these lipid biomarkers was found to predict relapse with the AUC of 0.861. A user-friendly smartphone application was developed to facilitate the straightforward "input-index, output-answer" screening process, enhancing both clinical decision-making and patient care. The diagnostic model based on the serum lipid-related indexes (TC, TG, LDL, HDL, ApoA1, and ApoB) may be the useful tool for NMOSD in diagnosis and monitoring of disease stage, thereby improving the treatment outcome for patients. Future studies should focus on integrating these biomarkers into routine clinical practice to realize their full potential in enhancing NMOSD management. Show less
📄 PDF DOI: 10.2147/JIR.S496018
APOB
Hongqin Li, Rong Xu, Liquan Xie +3 more · 2025 · Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research · SAGE Publications · added 2026-04-24
Bushen Huoxue Acupuncture shows potential in treating neurodegenerative diseases, but its mechanisms remain incompletely understood. Using the senescence-accelerated mouse-prone 8 (SAMP8) mouse model, Show more
Bushen Huoxue Acupuncture shows potential in treating neurodegenerative diseases, but its mechanisms remain incompletely understood. Using the senescence-accelerated mouse-prone 8 (SAMP8) mouse model, we assessed cognitive function via the Morris water maze test, hippocampal neuronal apoptosis with terminal deoxynucleotidyl transferase dUTP nick end labeling staining, and microglial activation through immunohistochemistry. Serum levels of inflammatory cytokines [tumor necrosis factor-alpha, interleukin (IL)-1β, and IL-6] were quantified by enzyme-linked immunosorbent assay. The expression of SIRT2 pathway-related proteins, along with Aβ deposition, was analyzed using Western blotting, immunohistochemistry, and immunofluorescence. The results demonstrated that Bushen Huoxue Acupuncture improved cognitive function in SAMP8 mice, reducing hippocampal neuronal apoptosis and decreasing serum levels of pro-inflammatory cytokines. Additionally, it reduced the levels of Aβ42, a more aggregation-prone and toxic Aβ subtype, in both hippocampal tissues and serum, as well as the number of CD68-positive cells in hippocampal tissues, suggesting the inhibition of amyloid pathology and neuroinflammatory. The treatment also downregulated SIRT2, BACE1, and APP-CTF while increasing RTN4B expression. Notably, Bushen Huoxue Acupuncture outperformed non-acupoint acupuncture in enhancing cognitive function and reducing inflammation. Our findings indicate that Bushen Huoxue Acupuncture alleviates cognitive deficits and neuroinflammation by suppressing the SIRT2-mediated RTN4B/BACE1 pathway, highlighting acupuncture as a promising therapy for neurodegenerative diseases. Show less
no PDF DOI: 10.1177/10799907251391519
BACE1
Shuzhi Zhao, Yili Zhang, Chenxin Li +2 more · 2025 · Biochemical and biophysical research communications · Elsevier · added 2026-04-24
The pyroptosis of retinal Müller cells is intricately linked to the pathogenesis of diabetic retinopathy (DR). Ubiquitin-fold modifier 1 (UFM1)-mediated UFMylation plays an important role in insulin a Show more
The pyroptosis of retinal Müller cells is intricately linked to the pathogenesis of diabetic retinopathy (DR). Ubiquitin-fold modifier 1 (UFM1)-mediated UFMylation plays an important role in insulin and diabetes mellitus metabolism and regulates cell death such as apoptosis and pyroptosis. UFM1-specific protease 2 (UFSP2) mediates the maturation of the UFM1 precursor and thus affects UFMylation reaction. However, its role in DR remains unknown. The aim of our study was to determine the mechanism and upstream regulation of UFSP2 on the pyroptosis of rat retinal Müller cells. Pathological changes, UFSP2 expression and succinate accumulation were determined in retinal tissues of db/db diabetic mice via Hematoxylin and eosin and immunofluorescence staining and biochemical analysis. High glucose (HG) was used to construct a DR cell model using rat retinal Müller cells (rMC-1). Ufsp2 RNA interference and overexpression plasmids were constructed to determine the effects of UFSP2. Pyroptosis and reactive oxygen species (ROS) levels were assessed via flow cytometry. Inflammatory cytokine (IL-1β and IL-18) levels and key molecular markers related to pyroptosis (NLRP3, ASC, Caspase-1p20, GSDMD-N) were measured by enzyme linked immunosorbent assay and Western blot, respectively. Succinate-mediated H3K3me3 enrichment in Ufsp2 promoter region was measured by chromatin immunoprecipitation. In vivo experiments revealed that the UFSP2 expression and succinate levels were increased in retinal tissues of db/db diabetic mice with thinning of retinal thickness. Moreover, in vitro experiments showed that The mRNA and protein levels of Ufsp2 exhibited a time-dependent increase under HG conditions. Upon Ufsp2 knockdown, the elevated oxidative stress, inflammatory responses, and pyroptosis stimulated by HG were significantly suppressed. The effect of Ufsp2 overexpression on pyroptosis and inflammatory responses was consistent with the HG stimulation, whereas the UFSP2-induced heightened levels of pyroptosis as well as the inflammatory state were significantly reversed when co-administered with NLRP3 inhibitor or ROS inhibitor. Further activating NLRP3 inflammasome using LPS + ATP stimulation revealed that the knockdown of Ufsp2 resulted in inhibited pyroptosis levels and inflammatory responses, while the Ufsp2 overexpression markedly increased pyroptosis and inflammatory responses. Lastly, succinate was demonstrated to influence Ufsp2 transcription, as well as the expression of H3K3me3 and its enrichment in the Ufsp2 promoter region, ultimately affecting pyroptosis and inflammatory responses. Succinate-mediated Ufsp2 transcription promotes pyroptosis in rMC-1 cells by activating NLRP3 inflammasome and oxidative stress. Show less
no PDF DOI: 10.1016/j.bbrc.2025.152614
RMC1
Yixin Zhai, Cheng Li, Xiang He +4 more · 2025 · Annals of medicine · Taylor & Francis · added 2026-04-24
Anoikis is a new mode of cell death that has been shown to correlate significantly with tumors. However, the clinical prognostic significance of anoikis in lung squamous cell carcinoma (LUSC) remains Show more
Anoikis is a new mode of cell death that has been shown to correlate significantly with tumors. However, the clinical prognostic significance of anoikis in lung squamous cell carcinoma (LUSC) remains poorly studied. The differentially expressed ARGs and candidate genes were selected by the differential analysis to construct a predictive model. Independent prognostic gene was determined by Cox and LASSO analysis and we used the HCC95 and NCI H520 cell line to verify the gene function. We used the data from TCGA, GEO, GeneCards, and Harmonizome databases to analyze the immune microenvironment, functional enrichment, and drug sensitivity analysis. We identified 717 differentially expressed and selected 3 ARGs (FADD, SNAI1, and BAG4) to construct a predictive model. We found that SNAI1 is an independent prognostic gene and confirmed that knocking out the SNAI1 inhibited the HCC95 We used ARGs to construct a prognosis model for LUSC that can accurately predict the prognosis of LUSC patients. ARGs, especially SNAI1, play an essential role in developing LUSC. These findings could provide individualized treatment plans and new research ideas for LUSC patients. Show less
no PDF DOI: 10.1080/07853890.2025.2514944
SNAI1
Kuangyang Chen, Yifeng Pan, Yaqiong Wang +8 more · 2025 · Journal of translational medicine · BioMed Central · added 2026-04-24
Atherosclerosis, a progressive inflammatory disease and the leading cause of cardiovascular disease (CVD), remains a global health burden due to the lack of effective early therapeutic interventions. Show more
Atherosclerosis, a progressive inflammatory disease and the leading cause of cardiovascular disease (CVD), remains a global health burden due to the lack of effective early therapeutic interventions. Although growing evidence highlights the involvement of plasma proteins in atherogenesis, their causal contributions to disease pathogenesis are poorly understood. To address this gap, we conducted a proteome-wide Mendelian randomization (MR) analysis using cis-pQTLs (cis-protein quantitative trait loci) from the deCODE and UKB-PPP cohorts (~90,000 individuals) as instrumental variables. We integrated colocalization analysis, summary-data-based MR (SMR), and HEIDI tests to systematically prioritize causal plasma proteins. Key findings were replicated in the CARDIOGRAMplusC4D (coronary artery disease, CAD) and FinnGen (CVD) cohorts. Functional validation was performed through phenome-wide association studies (PheWAS), single-cell transcriptomics, histological staining, and ELISA assays to characterize protein expression patterns in specific cell types and tissues. Among 2,711 plasma proteins analyzed, 28 showed strong genetic associations with atherosclerosis. Of these, five proteins (ADK, ANGPTL4, CD4, MGAT1, SYT11) met strict validation criteria through colocalization (posterior probability of colocalization, PP.H4 > 0.8) and SMR. Subsequent replication using MR and PheWAS further confirmed the causal roles of ADK, CALB2, and COMT in CAD and other CVD outcomes. Notably, CALB2 was specifically enriched in mast cells within atherosclerotic plaques and adipose tissue, and plasma levels were significantly elevated in patients with severe carotid artery stenosis (CAS). This study identifies 28 novel therapeutic targets for atherosclerosis using a rigorous multi-omics approach. Our findings establish CALB2 as a promising biomarker and therapeutic target, particularly in severe CAS, by linking genetic evidence to cell-type-specific expression and clinical phenotypes. These insights pave the way for precision medicine approaches in the prevention and treatment of CVD. The online version contains supplementary material available at 10.1186/s12967-025-07269-6. Show less
📄 PDF DOI: 10.1186/s12967-025-07269-6
ANGPTL4
Y H Wang, X X Zhang, Y H Guo +8 more · 2025 · Zhonghua wai ke za zhi [Chinese journal of surgery] · added 2026-04-24
no PDF DOI: 10.3760/cma.j.cn112139-20250221-00088
IL27
Yang Zhang, Jun Ma, Peipei Li +6 more · 2025 · Biomarker research · BioMed Central · added 2026-04-24
Fatty acids serve as a crucial energy source for tumor cells during the progression of chronic lymphocytic leukemia (CLL). The present study aims to elucidate the characteristics of fatty acid metabol Show more
Fatty acids serve as a crucial energy source for tumor cells during the progression of chronic lymphocytic leukemia (CLL). The present study aims to elucidate the characteristics of fatty acid metabolism (FAM) in CLL, construct a related prognostic score, and investigate the regulatory role and mechanisms of FAM in CLL development. Bulk RNA sequencing data from CLL patients and healthy controls were analyzed to identify differentially expressed fatty acid metabolic genes. FAM-score was constructed using Cox-LASSO regression and validated. Single-cell RNA sequencing was used to analyze the expression of key FAM genes in CLL immune cell subsets and investigate cellular communication. Functional assays, including cell viability, drug sensitivity, and oxygen consumption assays, were performed to assess the impact of fatty acid oxidation (FAO) inhibition on CLL cells. Three FAM-related genes (LPL, SOCS3, CNR1) were identified with independent prognostic significance to construct the risk score. The FAM-score demonstrated superior prognostic performance compared to the Binet stage and was associated with established clinical prognostic markers. Single-cell analysis revealed distinct expression patterns of LPL, SOCS3, and CNR1 across CLL immune cell subsets. Cellular communication analysis highlighted the regulatory role of distinct B cell and Treg subsets in the CLL microenvironment. CLL patients with high FAM-score displayed distinct immune infiltration patterns, with increased FAO pathway activity. Inhibition of FAO reduced CLL cell viability, synergistically enhanced the efficacy of the PI3K inhibitor idelalisib. The present study constructed a prognostic risk score based on FAM gene expression, revealing related immune phenotypic differences and exploring the regulatory role of FAO in CLL development. Targeting fatty acid metabolism potentially modulates the CLL immune microenvironment and synergistically enhances the efficacy of PI3K inhibitors. Show less
📄 PDF DOI: 10.1186/s40364-025-00753-7
LPL
Zejun Fan, Zhenyu Li, Yiqing Jin +9 more · 2025 · Life medicine · Oxford University Press · added 2026-04-24
Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. Human blastoids can be generated in large numbers, making them well-suited for high-th Show more
Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. Human blastoids can be generated in large numbers, making them well-suited for high-throughput screening. However, automated methods for evaluating and characterizing blastoid morphology are lacking. We developed a deep-learning model-deepBlastoid-for automated classification of live human blastoids using only brightfield images. The model processes 273.6 images per second with an average accuracy of 87%, which is further improved to 97% by integrating a Confidence Rate metric. deepBlastoid outperformed human experts in throughput while matching accuracy in blastoid classification. We demonstrated the utility of the model in two use cases: (i) systematic assessment of the effect of lysophosphatidic acid (LPA) on blastoid formation and (ii) evaluating the impact of dimethyl sulfoxide (DMSO) on blastoid formation. The evaluation results of deepBlastoid using over 10,000 images were consistent with the known drug effects and showed subtle but significant effects that might have been overlooked in manual assessments. The publicly available deepBlastoid model enables researchers to train customized models based on their imaging and protocols, providing an efficient, automated tool for blastoid classification with broad applications in research, drug screening, and Show less
📄 PDF DOI: 10.1093/lifemedi/lnaf026
LPA
Juan Shen, Weiming Liang, Ruizhen Zhao +33 more · 2025 · iMeta · Wiley · added 2026-04-24
The gut microbiota influences host immunity and metabolism, and changes in its composition and function have been implicated in several non-communicable diseases. Here, comparing germ-free (GF) and sp Show more
The gut microbiota influences host immunity and metabolism, and changes in its composition and function have been implicated in several non-communicable diseases. Here, comparing germ-free (GF) and specific pathogen-free (SPF) mice using spatial transcriptomics, single-cell RNA sequencing, and targeted bile acid metabolomics across multiple organs, we systematically assessed how the gut microbiota's absence affected organ morphology, immune homeostasis, bile acid, and lipid metabolism. Through integrated analysis, we detect marked aberration in B, myeloid, and T/natural killer cells, altered mucosal zonation and nutrient uptake, and significant shifts in bile acid profiles in feces, liver, and circulation, with the alternate synthesis pathway predominant in GF mice and pronounced changes in bile acid enterohepatic circulation. Particularly, autophagy-driven lipid droplet breakdown in ileum epithelium and the liver's zinc finger and BTB domain-containing protein (ZBTB20)-Lipoprotein lipase (LPL) (ZBTB20-LPL) axis are key to plasma lipid homeostasis in GF mice. Our results unveil the complexity of microbiota-host interactions in the crosstalk between commensal gut bacteria and the host. Show less
📄 PDF DOI: 10.1002/imt2.272
LPL
Chuang Yang, Yiyuan Sun, Yihan Li +1 more · 2025 · Environmental health and preventive medicine · added 2026-04-24
Cancer is a major public health concern, particularly among middle-aged and elderly populations, who are disproportionately affected by rising cancer incidence. Environmental pollution has been identi Show more
Cancer is a major public health concern, particularly among middle-aged and elderly populations, who are disproportionately affected by rising cancer incidence. Environmental pollution has been identified as a significant risk factor for cancer development. China's Carbon Emission Trading Policy (CETP), implemented in pilot regions since 2013, aims to reduce carbon emissions and improve air quality. This study evaluates the impact of CETP on pan-cancer incidence, with a focus on its effects on specific cancer types and vulnerable populations. This quasi-natural experiment utilized data from the China Health and Retirement Longitudinal Study (CHARLS) and environmental data from the China National Environmental Monitoring Center (2011-2018). A staggered difference-in-differences (DID) model was employed to estimate the impact of CETP on cancer incidence. Robustness tests, including parallel trend tests, placebo analysis, and entropy balancing, validated the findings. Subgroup analyses were performed to assess the policy's heterogeneous effects based on gender, Body Mass Index (BMI), and smoking status. CETP implementation significantly reduced the incidence of six cancer types: endometrial, cervical, gastric, esophageal, breast, and lung cancers. Overall, pan-cancer incidence significantly declined post-policy implementation (CETP × POST: -47.200, 95% CI: [-61.103, -33.296], p < 0.001). The policy demonstrated stronger effects in highly polluted areas and among individuals with poorer mental health. Subgroup analysis revealed that females, individuals with lower BMI, and non-smokers experienced more substantial benefits. CETP significantly reduces cancer incidence by improving environmental quality and influencing mental health, with particularly strong effects observed among high-risk populations. This study highlights the important role of environmental economic policies in mitigating cancer burden and promoting public health. Future research should further explore the long-term impacts of this policy and its applicability across different national and regional contexts. Show less
📄 PDF DOI: 10.1265/ehpm.24-00387
CETP
Huayun Huang, Longzhou Liu, Zhong Liang +5 more · 2025 · Scientific reports · Nature · added 2026-04-24
Natriuretic peptides (NPs) have an important role in lipid metabolism in skeletal muscle and adipose tissue in animals. C-type natriuretic peptide (CNP) is an important NP, but the molecular mechanism Show more
Natriuretic peptides (NPs) have an important role in lipid metabolism in skeletal muscle and adipose tissue in animals. C-type natriuretic peptide (CNP) is an important NP, but the molecular mechanisms that underlie its activity are not completely understood. Treatment of intramuscular fat (IMF) and subcutaneous fat (SCF) adipocytes with CNP led to decreased differentiation, promoted proliferation and lipolysis, and increased the expression of natriuretic peptide receptor B (NPRB) mRNA. Silencing natriuretic peptide C (NPPC) had the opposite results in IMF and SCF adipocytes. Transcriptome analysis found 665 differentially expressed genes (DEGs) in IMF adipocytes and 991 in SCF adipocytes. Seven genes in IMF adipocytes (FABP4, APOA1, ACOX2, ADIPOQ, CD36, FABP5, and LPL) and eight genes in SCF adipocytes (ACOX3, ACSL1, APOA1, CPT1A, CPT2, FABP4, PDPK1 and PPARα) are related to fat metabolism. Fifteen genes were found to be enriched in the peroxisome proliferator-activated receptor (PPAR) pathway. Integrated analysis identified 113 intersection genes in IMF and SCF adipocytes, two of which (APOA1 and FABP4) were enriched in the PPAR pathway. In conclusion, CNP may regulated lipid metabolism through the NPRB-PPAR pathway in both IMF and SCF adipocytes, FABP4 and APOA1 may be the key genes that mediated CNP regulation of fat deposition. Show less
📄 PDF DOI: 10.1038/s41598-025-86433-w
LPL
Yu-Fan Chen, Chien-Wei Lee, Yi-Shuan J Li +8 more · 2025 · Experimental & molecular medicine · Nature · added 2026-04-24
Macrophages play a crucial role in coordinating the skeletal muscle repair response, but their phenotypic diversity and the transition of specialized subsets to resolution-phase macrophages remain poo Show more
Macrophages play a crucial role in coordinating the skeletal muscle repair response, but their phenotypic diversity and the transition of specialized subsets to resolution-phase macrophages remain poorly understood. Here, to address this issue, we induced injury and performed single-cell RNA sequencing on individual cells in skeletal muscle at different time points. Our analysis revealed a distinct macrophage subset that expressed high levels of Gpnmb and that coexpressed critical factors involved in macrophage-mediated muscle regeneration, including Igf1, Mertk and Nr1h3. Gpnmb gene knockout inhibited macrophage-mediated efferocytosis and impaired skeletal muscle regeneration. Functional studies demonstrated that GPNMB acts directly on muscle cells in vitro and improves muscle regeneration in vivo. These findings provide a comprehensive transcriptomic atlas of macrophages during muscle injury, highlighting the key role of the GPNMB macrophage subset in regenerative processes. Our findings suggest that modulating GPNMB signaling in macrophages may represent a promising avenue for future research into therapeutic strategies for enhancing skeletal muscle regeneration. Show less
no PDF DOI: 10.1038/s12276-025-01467-4
NR1H3
Huizhen Zhang, Junjie Li, Heng Xu +3 more · 2025 · Current gene therapy · Bentham Science · added 2026-04-24
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) is a highly prevalent female malignancy. As the epigenomic characteristics of immune cells and cancer cells can serve as predict Show more
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) is a highly prevalent female malignancy. As the epigenomic characteristics of immune cells and cancer cells can serve as predictive indicators for the response to cancer immunotherapy, analysis of epigenetically modified genes (EpiGenes) could contribute to CESC treatment. The ssGSEA algorithm was employed to compute EpiGenes scores. Core genes that exhibited significant module association and a close correlation with EpiGenes scores were identified via the WGCNA package. Univariate Cox proportional hazards regression was performed on the core genes using the survival package, followed by gene set reduction via LASSO Cox regression. Ultimately, key genes were determined through multivariate Cox regression to establish a RiskScore model. Further, the optimal risk cutoff was determined using the survminer package to stratify CESC patients into high- and low-risk subgroups. For enrichment analysis, clusterProfiler and GSEA were utilized. Immune infiltration across risk groups was evaluated via ssGSEA, the MCPcounter algorithm, and the ESTIMATE algorithm. TIDE was employed to compare immunotherapeutic responses between the risk groups, while the pRRophetic software was utilized to predict patients' chemotherapeutic drug sensitivity. The biomarkers identified were validated by performing in vitro experiments. CEP78, DOCK7, DPY19L4, and POM121 were identified by computational analyses as the key genes for CESC and further validated through in vitro experiments. Pathway enrichment analysis revealed predominant enrichment in immune-related pathways in the high-risk group, whereas the low-risk group was more enriched in energy and metabolic pathways. A significant negative correlation was observed between CD8+ T cell abundance and RiskScore, with higher ESTIMATEScores and StromalScores in high-risk patients. Notably, the high-risk group also demonstrated lower potential sensitivity to immunotherapy but more active responsiveness to a broader spectrum of chemotherapeutic agents. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that module genes are significantly enriched in cell cycle regulatory pathways, and these genes, in conjunction with Human Papillomavirus (HPV) infection-induced cell cycle dysregulation, jointly participate in CESC pathogenesis, providing a mechanistic basis for understanding the disease. This study provided novel theoretical evidence for immunotherapy and chemotherapy selection in the management of CESC. Show less
no PDF DOI: 10.2174/0115665232432474251103064112
DOCK7
Xuehao Cui, Chao Sun, Dejia Wen +2 more · 2025 · Global heart · added 2026-04-24
Cardiovascular diseases (CVDs) are the leading global cause of mortality and disability, with prevalence increasing due to aging and risk factors like obesity and hypertension. The retina, rich in mic Show more
Cardiovascular diseases (CVDs) are the leading global cause of mortality and disability, with prevalence increasing due to aging and risk factors like obesity and hypertension. The retina, rich in microvasculature, provides a unique opportunity to investigate microvascular dysfunction linked to CVDs and other systemic vascular diseases. This study used a multifaceted approach to assess the genetic correlation and causal relationship between retinal characteristics and CVDs. Linkage disequilibrium score regression (LDSC) and Mendelian randomization (MR) analyses were conducted using genome-wide association study (GWAS) data from the UK Biobank and FinnGen datasets. A cross-sectional study was also conducted to validate the findings, collecting optical coherence tomography (OCT) images from 124 eyes (89 with CVDs and 35 healthy controls). A prediction model is based on least absolute shrinkage and selection operator (LASSO) regression to assess the risk of CVD. Using LDSC and two-sample MR, we found genetic evidence consistent with a causal effect whereby genetically proxied thinner retinal nerve fiber layer (RNFL) was associated with higher risks of hypertension and myocardial infarction (MI), while genetically proxied thicker photoreceptor inner segment/outer segment (PR-IS/OS) was associated with coronary heart disease and MI (false discovery rate [FDR] thresholds as reported). Genetically proxied thinner retinal pigment epithelium (RPE) showed an inverse association with stroke risk. Several circulating biomarkers-including lipoprotein(a) [Lp(a)], low-density lipoprotein cholesterol (LDL-C), and ApoB-exhibited MR evidence of association with multiple CVDs. In a cross-sectional cohort, retinal layer differences and their relationships with lipids were directionally consistent with the genetic findings. Retinal structural traits measured by OCT-particularly RNFL, PR-IS/OS, and RPE thickness-are best interpreted as non-invasive markers that reflect systemic vascular biology. Our MR analyses support shared etiologic pathways between retinal microstructure and CVDs rather than implying that retinal damage clinically causes cardiovascular events. Findings warrant validation in larger and more diverse populations and should not be considered definitive proof of causality. Show less
📄 PDF DOI: 10.5334/gh.1493
APOB