👤 Xiaoli Jiang

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873
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597
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Also published as: Aimin Jiang, Anan Jiang, Bao Jiang, Baoping Jiang, Bei Jiang, Bin Jiang, Bing-Hua Jiang, Bingdong Jiang, Bo Jiang, Bowen Jiang, Caiyun Jiang, Can Jiang, Cen Jiang, Changtao Jiang, Chao Jiang, Chao Qiang Jiang, Chaoqian Jiang, Chaoqiang Jiang, Charlie Jiang, Chen Jiang, Chen-Chen Jiang, Chen-Yang Jiang, Cheng Jiang, Cheng-Yan Jiang, Chengxian Jiang, Chengzhi Jiang, Chenke Jiang, Chenyang Jiang, Chongyi Jiang, Chuanhe Jiang, Chun-Guo Jiang, Chun-Lei Jiang, Chunhui Jiang, Chunmiao Jiang, Chunping Jiang, Chunqing Jiang, Chunyang Jiang, Congqing Jiang, Cui-Ping Jiang, Cuihua Jiang, Cuiping Jiang, Da Jiang, Dahai Jiang, Dan Jiang, Dandan Jiang, Danjie Jiang, Dawei Jiang, Deke Jiang, Dong Jiang, Dong-Neng Jiang, Dongmei Jiang, Dongsheng Jiang, Dongwen Jiang, Dongyang Jiang, F Jiang, Fan Jiang, Fang Jiang, Fangqin Jiang, Fei Jiang, Feng Jiang, Fengjuan Jiang, Fengli Jiang, Fengqi Jiang, Fengxian Jiang, Fengze Jiang, Fu-Sheng Jiang, Fuling Jiang, Gang Jiang, Gaowei Jiang, Gening Jiang, Guan-Min Jiang, Guang Jiang, Guang-Jian Jiang, Guanglong Jiang, Guangpeng Jiang, Guangyu Jiang, Guangzhen Jiang, Guannan Jiang, Gui-Yang Jiang, Guitao Jiang, Guiya Jiang, Guiyang Jiang, Guli Jiang, Guoheng Jiang, Guoliang Jiang, Guoqiang Jiang, Guoyan Jiang, Guozhi Jiang, H Jiang, Hai-He Jiang, Hai-Lu Jiang, Hai-Lun Jiang, Hai-ou Jiang, Haibo Jiang, Haifang Jiang, Haifeng Jiang, Haijun Jiang, Hailun Jiang, Haiping Jiang, Haiqiang Jiang, Haisong Jiang, Haixing Jiang, Haiyang Jiang, Haiying Jiang, Haizhen Jiang, Han Jiang, Han-Tao Jiang, Hanjie Jiang, Hanxue Jiang, Hao Jiang, Haowen Jiang, He Jiang, Hemin Jiang, Hequn Jiang, Hong Jiang, Hong-Li Jiang, Hong-Yan Jiang, Hong-liu Jiang, Hongcheng Jiang, Hongchi Jiang, Hongjing Jiang, Hongkun Jiang, Hongli Jiang, Hongxiang Jiang, Hongyu Jiang, Houbo Jiang, Hu Jiang, Hua Jiang, Huajun Jiang, Hualiang Jiang, Huanglei Jiang, Huanguo Jiang, Huanyu Jiang, Huanzhu Jiang, Huawei Jiang, Hugang Jiang, Hui Jiang, Hui-Hui Jiang, Huili Jiang, Huiqing Jiang, Huiyong Jiang, J Jiang, Jessica Li Jiang, Ji Jiang, Ji-yao Jiang, Jia Jiang, Jiahao Jiang, Jiahong Jiang, Jian Jiang, Jian-Dong Jiang, Jian-Gang Jiang, Jianan Jiang, Jiandong Jiang, Jianhua Jiang, Jianhui Jiang, Jianming Jiang, Jianrong Jiang, Jiansen Jiang, Jianwei Jiang, Jiaqi Jiang, Jiawei Jiang, Jiaxuan Jiang, Jie Jiang, Jie-Feng Jiang, Jieqing Jiang, Jieyi Jiang, Jiji Jiang, Jin Jiang, Jin-Yan Jiang, Jinfeng Jiang, Jing Jiang, Jing-Si Jiang, Jingbo Jiang, Jinghua Jiang, Jingjing Jiang, Jingwei Jiang, Jingwen Jiang, Jingyan Jiang, Jingzhou Jiang, Jinhong Jiang, Jinhua Jiang, Jinlan Jiang, Jinlun Jiang, Jinxia Jiang, Jinyun Jiang, Jishun Jiang, Jiwei Jiang, Jiyang Jiang, Jiyue Jiang, Jun Jiang, Jun-Jie Jiang, Junfang Jiang, K Jiang, Kai Jiang, Kang Jiang, Ke Jiang, Kele Jiang, Kuan Jiang, Kunyin Jiang, Kuo-Ching Jiang, L Jiang, Lai Jiang, Lan Jiang, Lan-Lan Jiang, Lei Jiang, Li Jiang, Li-Dan Jiang, Li-He Jiang, Li-Hong Jiang, Li-Rong Jiang, Li-Sha Jiang, Lianguang Jiang, Lianyong Jiang, Lihong Jiang, Lihuan Jiang, Lijing Jiang, Lijuan Jiang, Lijun Jiang, Lili Jiang, Lin Jiang, Ling Jiang, Ling-Xiang Jiang, Lingli Jiang, Linglin Jiang, Lingling Jiang, Linke Jiang, Linlin Jiang, Linying Jiang, Liping Jiang, Liqing Jiang, Lishi Jiang, Liuyan Jiang, Lixin Jiang, Liying Jiang, Long Jiang, Longying Jiang, Lu Jiang, Man Jiang, Mei Jiang, Meichen Jiang, Meichun Jiang, Meimei Jiang, Meixiu Jiang, Meng Jiang, Meng-Ting Jiang, Mengjie Jiang, Mengmeng Jiang, Mengqiang Jiang, Mengxi Jiang, Mengxue Jiang, Mengya Jiang, Mengzhu Jiang, Min Jiang, Ming Jiang, Ming-Rui Jiang, Mingchen Jiang, Minghao Jiang, Minghu Jiang, Mingshan Jiang, Mingxing Jiang, Mingyang Jiang, Minqing Jiang, Mona Zhi Ling Mai Jiang, Mouyan Jiang, Mujun Jiang, Nan Jiang, Nanying Jiang, Neng Jiang, Nengjing Jiang, Nili Jiang, Ning Jiang, Ou Jiang, Pan Jiang, Pan-Qiang Jiang, Pei Jiang, Peipei Jiang, Peng Jiang, Pengling Jiang, Ping Jiang, Ping-Ping Jiang, Pu Jiang, Qi Jiang, Qi-Chen Jiang, Qian Jiang, Qiang Jiang, Qianzhu Jiang, Qichen Jiang, Qicheng Jiang, Qin Jiang, Qing Jiang, Qing-Wu Jiang, Qing-Yan Jiang, Qinghua Jiang, Qingkun Jiang, Qingping Jiang, Qinyang Jiang, Qiu Jiang, Qiu-Le Jiang, Qiuxiao Jiang, Qiuyan Jiang, Qiwei Jiang, Qixia Jiang, Renjun Jiang, Rong Jiang, Rongqi Jiang, Rongtao Jiang, Rongyan Jiang, Roulan Jiang, Ru-Chao Jiang, Ruirui Jiang, Ruiwei Jiang, Rulang Jiang, Runqiu Jiang, Runshen Jiang, Runyang Jiang, S Q Jiang, Shali Jiang, Shan Jiang, Shan-Shan Jiang, Shanfeng Jiang, Shanshan Jiang, Shantong Jiang, Shaokai Jiang, Shaoping Jiang, Shaowen Jiang, Shaoxiong Jiang, Sharon Jiang, Sheng Jiang, Shengnan Jiang, Shengwang Jiang, Shengying Jiang, Shi Jiang, Shih Sheng Jiang, ShihSheng Jiang, Shimin Jiang, Shiqing Jiang, Shirui Jiang, Shiwen Jiang, Shou-Yin Jiang, Shoufang Jiang, Shoulei Jiang, Shouwen Jiang, Shu Jiang, Shu-Zhen Jiang, Shuai Jiang, Shuang Jiang, Shusuan Jiang, Shuying Jiang, Shuzhong Jiang, Si-Liang Jiang, Sicong Jiang, Simon W Jiang, Sixiong Jiang, Siyi Jiang, Siyu Jiang, Songhao Jiang, Su Jiang, Sujun Jiang, Susu Jiang, Suyu Jiang, T Jiang, Tao Jiang, Tengfei Jiang, Tengyong Jiang, Tian Jiang, Tianlin Jiang, Tianqi Jiang, Tianyu Jiang, Ting Jiang, Ting-Bo Jiang, Ting-Ting Jiang, Ting-Wang Jiang, Tingbo Jiang, Tingting Jiang, Tingyun Jiang, Tongcui Jiang, W Jiang, Wan-Sheng Jiang, Wangjie Jiang, Wanqing Jiang, Wei I Jiang, Wei Jiang, Wei-Cheng Jiang, Weibo Jiang, Weifan Jiang, Weihao Jiang, Weijun Jiang, Weimin Jiang, Weiqi Jiang, Weixi Jiang, Wen G Jiang, Wen Jiang, Wen-Hua Jiang, Wen-Ping Jiang, Wen-Qi Jiang, Wen-hui Jiang, Wencan Jiang, Wenjuan Jiang, Wenna Jiang, Wenqing Jiang, Wenrong Jiang, Wenyi Jiang, X Jiang, X L Jiang, Xia Jiang, Xian-Cheng Jiang, Xiang Jiang, Xiang-Jun Jiang, Xiangjun Jiang, Xiangning Jiang, Xianta Jiang, Xiao Jiang, Xiao-Cui Jiang, Xiao-Lan Jiang, Xiao-Wen Jiang, Xiao-dan Jiang, Xiaobing Jiang, Xiaocong Jiang, Xiaofei Jiang, Xiaofeng Jiang, Xiaohua Jiang, Xiaohui Jiang, Xiaojuan Jiang, Xiaolin Jiang, Xiaolu Jiang, Xiaomin Jiang, Xiaona Jiang, Xiaosong Jiang, Xiaotao Jiang, Xiaoting Jiang, Xiaowen Jiang, Xiaoxiao Jiang, Xiaoxue Jiang, Xiaoyan Jiang, Xiaoyi Jiang, Xiaoyu Jiang, Xihong Jiang, Xijing Jiang, Xin Jiang, Xinfeng Jiang, Xing Jiang, Xinghong Jiang, Xinglin Jiang, Xinhai Jiang, Xinlong Jiang, Xinwei Jiang, Xinyi Jiang, Xinyin Jiang, Xinyue Jiang, Xiong Jiang, Xiufeng Jiang, Xiulong Jiang, Xuanting Jiang, Xue Jiang, Xuejun Jiang, Xueli Jiang, Xuemei Jiang, Xueping Jiang, Xueqin Jiang, Xuexia Jiang, Xueying Jiang, Xuhong Jiang, Xun Jiang, Xunping Jiang, Xunwei Jiang, Y Jiang, Y-D Jiang, Ya-Ping Jiang, Yafei Jiang, Yali Jiang, Yamei Jiang, Yan Jiang, Yan-Yi Jiang, Yanan Jiang, Yanchao Jiang, Yanfang Jiang, Yanfeng Jiang, Yang Jiang, Yangfu Jiang, Yangyang Jiang, Yanji Jiang, Yanle Jiang, Yanming Jiang, Yanping Jiang, Yanshuang Jiang, Yanxin Jiang, Yanyan Jiang, Yanzhi Jiang, Yaofei Jiang, Yaona Jiang, Yaxi Jiang, Yazhuo Jiang, Yexiang Jiang, Yi Jiang, Yi-Xue Jiang, Yiao Jiang, Yida Jiang, Yilin Jiang, Yinan Jiang, Ying Jiang, Ying-Ming Jiang, Yingjie Jiang, Yingsong Jiang, Yingying Jiang, Yinhui Jiang, Yiran Jiang, Yiting Jiang, Yitong Jiang, Yong Fang Jiang, Yong Jiang, Yong-Li Jiang, Yong-Qing Jiang, Yong-Sheng Jiang, Yonghong Jiang, Yonghui Jiang, Yongliang Jiang, Yongpo Jiang, Yongqing Jiang, You-Hua Jiang, Youde Jiang, Youhai Jiang, Youming Jiang, Yu Jiang, Yu-Hang Jiang, Yu-Jia Jiang, Yu-Lin Jiang, Yu-Xuan Jiang, Yu-ping Jiang, Yuan Jiang, Yuanjun Jiang, Yuanyuan Jiang, Yue Jiang, Yue-Ming Jiang, Yue-Ping Jiang, Yuecheng Jiang, Yueping Jiang, Yuer Jiang, Yufeng Jiang, Yuhan Jiang, Yuhang Jiang, Yuhui Jiang, Yumin Jiang, Yun-Jin Jiang, Yunjing Jiang, Yunliang Jiang, Yunsheng Jiang, Yunxiu Jiang, Yunzhe Jiang, Yupeng Jiang, Yutao Jiang, Yuteng Jiang, Yuting Jiang, Yuwei Jiang, Yuwu Jiang, Z Gordon Jiang, Z Jiang, Z Y Jiang, Z-Y Jiang, Ze-Bin Jiang, Zesong Jiang, Zetan Jiang, Zeyu Jiang, Zhao Jiang, Zhao-Yan Jiang, Zhaodi Jiang, Zhaoshi Jiang, Zhen Jiang, Zheng Jiang, Zheng-Yuan Jiang, Zhengfan Jiang, Zhenghui G Jiang, Zhengming Jiang, Zhengqiao Jiang, Zhengwen Jiang, Zhengwu Jiang, Zhengxuan Jiang, Zhengyi Jiang, Zhentao Jiang, Zhi-Sheng Jiang, Zhi-Yan Jiang, Zhi-Ying Jiang, Zhichao Jiang, Zhicong Jiang, Zhiwei Jiang, Zhixia Jiang, Zhixin Jiang, Zhiying Jiang, Zhongshan Jiang, Zi-Hua Jiang, Zichao Jiang, Zipei Jiang, Ziqin Jiang, Ziyi Jiang, Ziying Jiang, Ziyu Jiang, Zong-Zhe Jiang
articles
Na Liu, Hongli Zeng, Xiangsheng Cai +6 more · 2025 · Frontiers in genetics · Frontiers · added 2026-04-24
To investigate the association between polymorphisms of the A case-control study was conducted, enrolling 100 HTG patients and 100 age-matched controls with normal triglyceride levels from the physica Show more
To investigate the association between polymorphisms of the A case-control study was conducted, enrolling 100 HTG patients and 100 age-matched controls with normal triglyceride levels from the physical examination cohort at Guangzhou 11th People's Hospital (January-December 2023) The observation group showed significant differences in genotype frequencies of Show less
📄 PDF DOI: 10.3389/fgene.2025.1654501
APOA5
Tao Zhang, Siyu Yang, Haijun Jiang +7 more · 2025 · ZooKeys · added 2026-04-24
The genus
📄 PDF DOI: 10.3897/zookeys.1262.164459
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Ricardo Hernandez Arriaza, Dylan Reil, Nina Fatuzzo +7 more · 2025 · Biochemistry · ACS Publications · added 2026-04-24
The brain is the most cholesterol-rich organ in the body, and ApoE is the main lipid carrier protein in the brain. Although very little, if any, ApoE exists in its apoprotein form in physiological flu Show more
The brain is the most cholesterol-rich organ in the body, and ApoE is the main lipid carrier protein in the brain. Although very little, if any, ApoE exists in its apoprotein form in physiological fluids, recombinant ApoE is typically prepared in a lipid-free state to study its physiological functions. We describe a lipid nanoparticle (LNP) form of ApoE as a primary extracellular product of the eukaryotic protein export system. Whereas the apoprotein is the dominant secreted product when the Show less
📄 PDF DOI: 10.1021/acs.biochem.5c00503
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Xuan Bai, Dingzi Zhou, Jing Luo +14 more · 2025 · Medicine · added 2026-04-24
Lipid metabolism abnormalities and inflammation have been implicated in gallstone disease (GSD) development, but the causal relationships and potential mediation effects among lipid metabolites, infla Show more
Lipid metabolism abnormalities and inflammation have been implicated in gallstone disease (GSD) development, but the causal relationships and potential mediation effects among lipid metabolites, inflammatory factors, and GSD remain unclear. The aim of this study is to explore the causal relationships among these 3 factors. This study employed 2-sample Mendelian Randomization (TSMR) and 2-step MR to investigate the causal relationships and potential mediation effects among 91 inflammatory factors, 6 lipid metabolism-related molecules (HDL-C, LDL-C, TG, total cholesterol, ApoA1, and ApoB), and GSD. We opted for 4 distinct MR analysis methods including inverse variance weighted method, weighted median method, MR-Egger regression method and MR-PRESSO analysis. Sensitivity analyses included MR-Egger intercept tests, Cochran's Q statistic, Steiger tests, and leave-one-out analyses. Product of coefficients method was used to estimate mediation proportion. TSMR analysis revealed that every 1-unit increase in low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB), the risk of GSD decreased by 16.5%, 10.2%, 8.4%, and 13.1%, respectively. Inflammatory factors such as Natural killer cell receptor 2B4 (CD244), Macrophage colony-stimulating factor 1 (CSF-1), and interleukin-18 receptor 1 (IL-18R1) were identified as risk factors for GSD, while Fibroblast growth factor 19 levels (FGF19), Interleukin-1-alpha levels (IL-1α), and Interleukin-8 levels (IL-8) were found to be protective. Mediation analysis through 2-step MR identified potential pathways involving ApoA1--IL-8--GSD (P = .084) and IL-1α--ApoB--GSD (P = .117). This study provides robust evidence of causal links between specific lipid metabolites and GSD, as well as suggestive causal associations for several inflammatory factors. However, mediation analysis did not support significant roles for lipids or inflammatory factors as mediators in GSD pathogenesis. Future research could be further pursued in areas such as drug target intervention and mechanistic studies. Show less
no PDF DOI: 10.1097/MD.0000000000044704
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Pu Jiang, Liangyu Liu, Lixian Chen +2 more · 2025 · Pharmaceuticals (Basel, Switzerland) · MDPI · added 2026-04-24
📄 PDF DOI: 10.3390/ph18091280
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Chenfeng Zou, Bei Yang, Jiaying Zhang +5 more · 2025 · Phenomics (Cham, Switzerland) · Springer · added 2026-04-24
Emerging lipid-modifying agents show potential but lack evidence for the management of uric acid and gout. We aimed to explore the causal effects of lipid traits, lipid-modifying drugs on uric acid le Show more
Emerging lipid-modifying agents show potential but lack evidence for the management of uric acid and gout. We aimed to explore the causal effects of lipid traits, lipid-modifying drugs on uric acid levels and risk of gout. Two-sample MR analyses were performed to investigate the associations of genetically predicted lipid traits (LDL-C, HDL-C and TG) and lipid-modifying drug targets (PCSK9, HMGCR, NPC1L1, CETP, ABCG5/G8, APOB, LDLR, LPL, ANGPTL3, and APOC3) with uric acid levels and gout risk. Validation analyses were performed using the independent cohort of the UK Biobank. Summary-data-based MR was further conducted to estimate the associations of the expression of drug target genes with the outcomes. Genetically predicted lower HDL-C and higher TG were significantly associated with elevated uric acid levels ( The online version contains supplementary material available at 10.1007/s43657-024-00212-7. Show less
no PDF DOI: 10.1007/s43657-024-00212-7
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Qin Jiang, Tao Yang, Hao Yang +9 more · 2025 · Biomolecules · MDPI · added 2026-04-24
(1) Objective: This study aimed to systematically elucidate the molecular mechanisms by which gypenosides (GP), a major active component of
📄 PDF DOI: 10.3390/biom15081205
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Mei-Zhen Zhang, Jing Zheng, Li-Ting Cai +9 more · 2025 · Comparative biochemistry and physiology. Part D, Genomics & proteomics · Elsevier · added 2026-04-24
Scatophagus argus is a highly valuable aquaculture fish. Its artificial breeding faces problems in the induction of high quality eggs, thus necessitating studies on the regulation of ovarian developme Show more
Scatophagus argus is a highly valuable aquaculture fish. Its artificial breeding faces problems in the induction of high quality eggs, thus necessitating studies on the regulation of ovarian development. As the centre of nutrient metabolism in fish, the liver provides the material basis for ovarian development. However, the molecular mechanism of the liver in ovarian development in S. argus is still unclear. In this study, a transcriptome analysis of adult S. argus livers at different stages of ovarian development (stages II, III and IV) was performed. 410, 1025 and 1867 differentially expressed genes (DEGs) were obtained between stages II and III, stages II and IV and stages III and IV, respectively. In GO and KEGG analyses, DEGs were mostly involved in vitellogenesis and egg envelope formation (e.g., erα, erβ1, vtga, vtgb, vtgc, zp3, zp4a and zp4b), lipid metabolism and energy metabolism (e.g., dagt1, dagt2, lpl, apob, hk1, acly, ogdh, pc, and fbp1), and hormone signaling (e.g., lepa and igfbp1). Additionally, genes that were significantly upregulated in the liver at stage IV of ovarian development, compared to stages II and III, were markedly enriched in steroid biosynthesis and metabolism pathways. These findings provide clues to understanding the mechanisms of liver action in teleost ovarian development. Show less
no PDF DOI: 10.1016/j.cbd.2025.101550
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Xiao-Yan Shi, Ya-Kun Liu, Yan Chen +3 more · 2025 · Pediatric obesity · Blackwell Publishing · added 2026-04-24
Metabolic dysfunction-associated steatotic liver disease (MASLD) has become a prevalent liver condition in children and teenagers with obesity. Unfortunately, there is no standardized treatment. To ex Show more
Metabolic dysfunction-associated steatotic liver disease (MASLD) has become a prevalent liver condition in children and teenagers with obesity. Unfortunately, there is no standardized treatment. To examine the connection between apolipoprotein B (apoB), apolipoprotein A1 (apoA1), and the apoB/apoA1 ratio with the occurrence of MASLD in this population. A retrospective study was made on children and adolescents with obesity in a children's hospital between the period 2020 and 2022. Anthropometric data, ultrasound results, and blood biochemistry were analysed to assess the connection between apoB, apoA1, and the presence of MASLD. Of the 916 participants included, 313 were diagnosed with MASLD. The level of serum apoB reflected a substantial dose-response correlation with the odds of having MASLD. When apoB levels exceeded the 50th percentile, the risk increased significantly, and at the 95th percentile, the odds were 4.83 times higher than at the 50th percentile (95% CI: 2.02-11.56). The ratio of apoB/apoA1 at the 95th percentile was connected to a 2.41-fold higher prevalence compared to the 50th percentile (95% CI: 1.33-4.37). No significant correlation was found between the levels of apoA1 and MASLD prevalence. Elevated levels of apoB and the apoB/apoA1 ratio have been strongly connected to increased MASLD prevalence in children and adolescents with obesity; hence, signifying their potential usefulness as biomarkers for early detection and intervention. Show less
no PDF DOI: 10.1111/ijpo.70017
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Lili Yang, Jingjing Zhang, Jiangyan Han +1 more · 2025 · Clinical and experimental hypertension (New York, N.Y. : 1993) · Taylor & Francis · added 2026-04-24
Contributing factors for the development of heart failure (HF) involve both apolipoprotein B (ApoB) and coronary microvascular dysfunction (CMD). Although ApoB has been linked to diverse cardiovascula Show more
Contributing factors for the development of heart failure (HF) involve both apolipoprotein B (ApoB) and coronary microvascular dysfunction (CMD). Although ApoB has been linked to diverse cardiovascular risks, its association with CMD remains unclear. A total of 145 patients undergoing cardiac single-photon emission computed tomography (SPECT) scan was enrolled into this retrospective study. Based on ApoB serum level, all subjects were classified into three groups (Group 1-3). Myocardial flow reserve (MFR) was calculated using myocardial blood flow (MBF) tested in different contexts. ApoB serum level was positively correlated to rest MBF but inversely associated with stress MBF and MFR. Following adjustment for covariates, a significant relationship was observed between increased ApoB and decreased MFR. The predictive value of ApoB was test by Receiver Operating Characteristic Curve (ROC) analysis, showing an area under curve (AUC) of 0.87. The findings indicated that a higher level of ApoB correlated with the severity of CMD. Show less
no PDF DOI: 10.1080/10641963.2025.2477651
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Jiawei Li, Ximei Li, Jiamin Tian +5 more · 2025 · Frontiers in veterinary science · Frontiers · added 2026-04-24
Lower intramuscular fat (IMF) and excessive abdominal fat reduce carcass quality in broilers. The study aimed to investigate the effects of dietary VD
📄 PDF DOI: 10.3389/fvets.2025.1542637
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Qiuxiao Jiang, Bin Feng, Yanhua Zhao +5 more · 2025 · Clinica chimica acta; international journal of clinical chemistry · Elsevier · added 2026-04-24
Lipoprotein subclasses and high-density lipoprotein (HDL) functions are associated with atherosclerotic cardiovascular disease (ASCVD), but researches on them in patients with nephrotic syndrome (NS) Show more
Lipoprotein subclasses and high-density lipoprotein (HDL) functions are associated with atherosclerotic cardiovascular disease (ASCVD), but researches on them in patients with nephrotic syndrome (NS) are limited. The aims of this study were (1) to analyze the changes in quantity and quality of lipoprotein in patients with idiopathic nephrotic syndrome (INS) and patients in remission from NS, and (2) to evaluate the lipid-related atherosclerotic risk in these patients. 51 patients with idiopathic nephrotic syndrome (NS group), 72 NS patients with complete remission (NS remission group), and 80 healthy controls (control group) were recruited. The levels of conventional lipids, lipoprotein subclasses, including VLDL, IDL (C, B, A), LDL (LDL1-7), HDL (large, intermediate, small) and HDL cholesterol efflux capacity (CEC), were measured and compared across the three groups. Conventional lipid parameters [TG, TC, LDL-C, apo-B and Lp(a)] and lipoprotein subclasses (VLDL, IDL-C, IDL-B, LDL-2 and sdLDL) were higher in NS group when compared to NS remission group and control group (P < 0.05). CEC in NS group was significantly lower than that in control group [21.0 (18.3-27.2) % vs 25.7 (23.3-28.9) %] (P < 0.001) and improved to 22.8 (20.6-23.7) % in NS remission group with the disease recovery. Proatherogenic changes in conventional lipid parameters, lipoprotein subclasses and HDL-CEC were observed in patients with NS, suggesting that more rigorous lipid regulation strategies may help reduce cardiovascular disease risk in patients with NS. Show less
no PDF DOI: 10.1016/j.cca.2025.120206
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Junhua Wu, Ming Qin, Yue Gao +5 more · 2025 · International journal of environmental health research · Taylor & Francis · added 2026-04-24
Previous studies found relationship between fluoride exposure and lipid metabolism. In present study, a cross-sectional study was conducted. Urinary fluoride concentrations and lipid metabolism indica Show more
Previous studies found relationship between fluoride exposure and lipid metabolism. In present study, a cross-sectional study was conducted. Urinary fluoride concentrations and lipid metabolism indicators were tested. Single nucleotide polymorphisms of ATP2B1 were sequenced. The median of urinary fluoride was 1.32 mg/L. Urinary fluoride was positively associated with the decrease in serum ApoA1 (OR = 1.48 [95% CI, 1.27-1.72]), inversely with ApoB elevation (OR = 0.69 [95% CI, 0.59-0.80]). Rs12817819 with carriers of T allele was associated with the decrease in serum ApoA1 (OR = 0.46 [95% CI, 0.26-0.81]), but inversely in rs17249754 with carriers for A allele (OR = 1.48 [95% CI, 1.07-2.06]) and rs7136259 with carriers for T allele (OR = 1.70 [95% CI, 1.22-2.37]). There was an interaction between urinary fluoride which was lower than 0.9 mg/L and rs7136259 for carriers of T allele (OR = 2.67 [95% CI, 1.34-5.31]) in serum ApoA1 decrease. It indicated fluoride exposure might be associated with the alteration of serum ApoA1 and ApoB in adults. Show less
no PDF DOI: 10.1080/09603123.2025.2466674
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Ze-Yuan Yin, Shi-Min He, Xin-Yuan Zhang +16 more · 2025 · Acta pharmacologica Sinica · Nature · added 2026-04-24
Ovarian cancer presents a significant treatment challenge due to its insidious nature and high malignancy. As autophagy is a vital cellular process for maintaining homeostasis, targeting the autophagi Show more
Ovarian cancer presents a significant treatment challenge due to its insidious nature and high malignancy. As autophagy is a vital cellular process for maintaining homeostasis, targeting the autophagic pathway has emerged as an avenue for cancer therapy. In the present study, we identify apolipoprotein B100 (ApoB100), a key modulator of lipid metabolism, as a potential prognostic biomarker of ovarian cancer. ApoB100 functioned as a tumor suppressor in ovarian cancer, and the knockdown of ApoB100 promoted ovarian cancer progression in vivo. Moreover, ApoB100 blocked autophagic flux, which was dependent on interfering with the lipid accumulation/endoplasmic reticulum (ER) stress axis. The effects of LFG-500, a novel synthetic flavonoid, on ApoB100 induction were confirmed using proteomics and lipidomics analyses. Herein, LFG-500 induced lipid accumulation and ER stress and subsequently blocked autophagy by upregulating ApoB100. Moreover, data from in vivo experiments further demonstrated that ApoB100, as well as the induction of the lipid/ER stress axis and subsequent blockade of autophagy, were responsible for the anti-tumor effects of LFG-500 on ovarian cancer. Hence, our findings support that ApoB100 is a feasible target of ovarian cancer associated with lipid-regulated autophagy and provide evidence for using LFG-500 for ovarian cancer treatment. Show less
no PDF DOI: 10.1038/s41401-024-01470-x
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Yi Jiang, Lantian Zhang, Dongyi Shen +1 more · 2025 · Endocrine · Springer · added 2026-04-24
The existing evidence regarding the impact of tamoxifen on lipoprotein(a) and apolipoproteins remains inconsistent. Therefore, this updated meta-analysis of randomized controlled trials (RCTs) aims to Show more
The existing evidence regarding the impact of tamoxifen on lipoprotein(a) and apolipoproteins remains inconsistent. Therefore, this updated meta-analysis of randomized controlled trials (RCTs) aims to enhance the quality of evidence concerning the effects of tamoxifen on these lipid parameters. Eligible RCTs published up to October 2024 were meticulously selected through a comprehensive search. A meta-analysis was then performed using a random-effects model, and results were presented as the weighted mean difference (WMD) with a 95% confidence interval (CI). Findings from the random-effects model revealed an increase in ApoA-I (WMD: 15.22 mg/dL, 95% CI: 6.43-24.01, P = 0.001), alongside decreases in ApoB (WMD: -9.33 mg/dL, 95% CI: -15.46 to -3.19, P = 0.003) and lipoprotein(a) (WMD: -3.35 mg/dL, 95% CI: -5.78 to -0.91, P = 0.007) levels following tamoxifen treatment in women. Subgroup analyses indicated a more significant reduction in lipoprotein(a) levels in RCTs with a duration of ≤24 weeks (WMD: -3.65 mg/dL) and in studies using tamoxifen doses of ≥20 mg/day (WMD: -4.53 mg/dL). This meta-analysis provides evidence that tamoxifen leads to a decrease in lipoprotein(a) levels, along with reductions in ApoB and increases in ApoA-I among women. Show less
📄 PDF DOI: 10.1007/s12020-024-04128-0
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Yuhui Lai, Shaozhao Zhang, Yue Guo +11 more · 2025 · American heart journal · Elsevier · added 2026-04-24
Elevated lipoprotein(a) (Lp[a]) and apolipoprotein B (apoB) are individually associated with the risk of atherosclerotic cardiovascular disease (ASCVD). Moreover, previous basic research has implicate Show more
Elevated lipoprotein(a) (Lp[a]) and apolipoprotein B (apoB) are individually associated with the risk of atherosclerotic cardiovascular disease (ASCVD). Moreover, previous basic research has implicated the potential interaction between apoB and Lp(a) in the atherogenic process. We aimed to determine whether apoB levels significantly modulate ASCVD risk associated with Lp(a) in a large community-based population without baseline cardiovascular disease. Plasma Lp(a) and apoB were measured in the Atherosclerosis Risk in Communities (ARIC) study. Elevated Lp(a) was defined as the highest race-specific quintile, and elevated apoB was defined as ≥89 mg/dl (median value). The modifying effect of apoB on the Lp(a)-related risk of ASCVD and coronary heart disease (CHD) was determined using Cox regression models adjusted for cardiovascular risk factors. Among 12,988 ARIC participants, 3,888 ASCVD events and 1754 CHD events were observed. Elevated apoB (≥89 mg/dl) and elevated Lp(a) (race-specific quintile 5) were independently associated with ASCVD (hazard ratio [HR]: 1.19; 95% CI: 1.08-1.30; P <0.001; HR: 1.27; 95% CI: 1.16-1.40; P < .001, respectively). Lp(a)-by-apoB interaction was noted [Lp(a) (quintile 1-4 or quintile 5) * apoB (<89 or ≥89 mg/dl) = 0.002]. Compared to the concordantly low Lp(a) group, the individuals with high Lp(a) had a greater ASCVD risk only when apoB was elevated (HR: 1.48; 95% CI: 1.34-1.63; P < .001). In the context of primary prevention, ASCVD risk associated with Lp(a) was observed only when apoB was elevated. The measurement of apoB can further refine and contextualize the ASCVD risk associated with Lp(a). Show less
no PDF DOI: 10.1016/j.ahj.2024.11.014
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Zufa Zhang, Long Lv, Sheng Guan +6 more · 2025 · Journal of affective disorders · Elsevier · added 2026-04-24
Depression is a pervasive mental illness that has a significant impact on public health globally. This study aimed to identify risk factors for depression and elucidate their causal relationships. Usi Show more
Depression is a pervasive mental illness that has a significant impact on public health globally. This study aimed to identify risk factors for depression and elucidate their causal relationships. Using data from the National Health and Nutrition Examination Survey (NHANES) and Genome-Wide Association Studies (GWAS). Serum ApoB was log-transformed and further divided into 4 groups. Multifactorial logistic regression analysis was used to assess the relationship between serum ApoB and depression. Subgroup analyses and interaction tests were used to observe the stability of the association between them. Smooth curve fitting was used to investigate nonlinear correlations. The causal effect of serum ApoB on depression was assessed using Mendelian randomization (MR) analysis. A total of 6531 participated in the study. After adjusting for all covariates, serum ApoB levels were positively associated with depression after adjustment for all covariates (OR = 1.40, 95 % CI = 1.06-1.84; P = 0.0176). Unfortunately, there was no significant causal relationship between serum ApoB and depression (OR = 0.9985,95 % CI = 0.9962-1.0008; P = 0.1923). Sensitivity analysis verified the reliability of the results. Serum ApoB was positively associated with an increased risk of depression, but MR analysis did not show a genetic causal relationship between ApoB and depression. Based on the results of the current study, no indication maintaining high levels of ApoB contributes to the management of depression. The main limitation of this study is the inconsistency of the cross-sectional study and the MR population. Show less
no PDF DOI: 10.1016/j.jad.2024.11.055
APOB
Lei Wu, Zhong Zhuang, Wenqian Jia +7 more · 2025 · Poultry science · Elsevier · added 2026-04-24
Residual feed intake (RFI) has recently gained attention as a key indicator of feed efficiency in poultry. In this study, 800 slow-growing ducks with similar initial body weights were reared in an exp Show more
Residual feed intake (RFI) has recently gained attention as a key indicator of feed efficiency in poultry. In this study, 800 slow-growing ducks with similar initial body weights were reared in an experimental facility until they were culled at 42 d of age. Thirty high RFI (HRFI) and 30 low RFI (LRFI) birds were selected to evaluate their growth performance, carcass characteristics, and muscle development. Transcriptome and weighted gene co-expression correlation network analyses of pectoral muscles were conducted on six LRFI and six HRFI ducks. The results revealed that selecting for LRFI significantly reduced feed consumption (P < 0.05) and improved feed efficiency without affecting the growth performance, slaughter rate, or meat quality of ducks (P > 0.05). Moreover, compared with HRFI ducks, LRFI ducks had a lower pectoral muscle fat content (P < 0.05), larger muscle fiber diameter and area (P < 0.05), and lower muscle fiber density (P < 0.05). There were significant differences in gene expression between LRFI and HRFI ducks, with 102 upregulated and 258 downregulated genes, which were enriched in the PPAR signaling pathway, adipocytokine signaling pathway, actin cytoskeleton regulation, ECM-receptor interaction, and focal adhesion. The expression of genes associated with fat and energy metabolism, including ACSL6, PCK1, APOC3, HMGCS2, PRKAG3, and G6PC1, was downregulated in LRFI ducks, and weighted gene co-expression correlation network analysis identified PRKAG3 as a hub gene. Our findings indicate that reduced mitochondrial energy metabolism may contribute to the RFI of slow-growing ducks, with PRKAG3 playing a pivotal role in this biological process. These findings provide novel insights into the molecular changes underlying RFI variation in slow-growing ducks. Show less
📄 PDF DOI: 10.1016/j.psj.2024.104613
APOC3
Min Zhao, Jiwei Jiang, Linlin Wang +8 more · 2025 · Frontiers in neuroscience · Frontiers · added 2026-04-24
Although previous studies have reported associations between gonadotropins, testosterone, and Alzheimer's disease (AD), their longitudinal relationships with cognitive decline and temporal lobe atroph Show more
Although previous studies have reported associations between gonadotropins, testosterone, and Alzheimer's disease (AD), their longitudinal relationships with cognitive decline and temporal lobe atrophy remain insufficiently characterized. This study examined the association between baseline hormone levels and cognitive decline and temporal lobe volume loss trajectories, and whether these associations vary by sex or This study included 490 participants (378 MCI/112 AD; 311 men/179 women; mean age = 75.01 ± 7.52) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Baseline plasma levels of gonadotropins (FSH, LH) and total testosterone (TT) were measured using Luminex xMAP multiplex immunoassay. Cognitive decline was assessed longitudinally through MMSE and ADAS-Cog 13 scores. Temporal lobe atrophy was quantified using tensor-based morphometry of 1.5T MRI scans, with bilateral temporal lobe volumes scaled to a normalized reference (1,000 = baseline). Linear mixed effects models were employed to relate baseline plasma hormones to longitudinal cognitive performance and temporal lobe volume. Longitudinal analyses showed that higher baseline FSH levels were associated with faster cognitive decline (MMSE: β = -0.025, The results indicate that in individuals across the AD spectrum, elevated gonadotropin levels may exert deleterious, domain-specific effects on cognitive decline or temporal lobe atrophy. Women with lower TT levels may experience faster cognitive progression. Although future studies incorporating additional longitudinal hormone measurements and cognitive trajectories are warranted, our results underscore the importance of gonadotropins and testosterone in AD progression. Show less
📄 PDF DOI: 10.3389/fnins.2025.1696274
APOE
Shizuka Hayashi, Jiyang Jiang, Yang Song +5 more · 2025 · The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · Elsevier · added 2026-04-24
To examine cross-sectional and longitudinal associations between vascular risk factors, APOE genotype, and perivascular spaces (PVS), with attention to sex- and region-specific patterns in older adult Show more
To examine cross-sectional and longitudinal associations between vascular risk factors, APOE genotype, and perivascular spaces (PVS), with attention to sex- and region-specific patterns in older adults. Population-based observational study using automated PVS quantification and multivariable regression models. UK Biobank, a large prospective cohort study of community-dwelling adults across the United Kingdom. A total of 38,121 participants (aged 47-90) were included cross-sectionally, and 4,225 longitudinally (mean follow-up 2.61 ± 1.0 years). A deep learning model was applied to brain MRI to quantify PVS in the basal ganglia (BG) and centrum semiovale (CSO). Vascular risk factors included hypertension, hypercholesterolemia, obesity, diabetes, smoking, and alcohol consumption. Models were adjusted for age, sex, scanner, and APOE-ɛ4 carrier status. Cross-sectionally, hypertension (b = 0.089, 95% CI = 0.069-0.108), hypercholesterolemia (b = 0.043, 95% CI = 0.017-0.064), obesity (b = 0.040, 95% CI = 0.016-0.064), and smoking (b = 0.056, 95% CI = 0.037-0.074) were associated with more BG-PVS. APOE-ɛ4 carriers (b = 0.039, 95% CI = 0.0015-0.076) and hypertension (b = 0.093, 95% CI = 0.056-0.130) were linked to more CSO-PVS. Moderate alcohol intake was associated with fewer BG-PVS in males but was associated with higher BG-PVS in females. Longitudinally, risk factor associations with PVS were limited. These findings support the utility of PVS as a biologically meaningful indicator of vascular brain health, with potential relevance for early identification of neurodegenerative risk in older adults. Show less
no PDF DOI: 10.1016/j.jagp.2025.11.016
APOE
Wenqing Wang, Yue Jiang, Xuan Pan +5 more · 2025 · Cell death & disease · Nature · added 2026-04-24
Atherosclerosis (AS) is a prevalent chronic arterial disease characterized by excessive cholesterol accumulation in the arterial intima. While substantial progress has been made in elucidating its ris Show more
Atherosclerosis (AS) is a prevalent chronic arterial disease characterized by excessive cholesterol accumulation in the arterial intima. While substantial progress has been made in elucidating its risk factors and pathogenesis, the upstream signaling molecules that drive the initiation and progression of AS remain poorly understood. Analysis of monocyte samples from the GSE23746 database revealed that Histone Deacetylase 6 (HDAC6) expression was significantly downregulated in patients with carotid atherosclerosis compared to healthy controls. In vitro experiments further demonstrated that HDAC6 deficiency markedly promotes foam cell formation in macrophages, a process dependent on its deacetylase activity. Mechanistically, HDAC6 interacts with signal transducer and activator of transcription 3 (STAT3) and regulates its acetylation at K685, a critical modification that facilitates macrophage foam cell formation. Specifically, the loss of HDAC6-mediated deacetylation leads to increased STAT3-K685 acetylation, which in turn upregulates the expression of CD36 and SRA, thereby enhancing cholesterol uptake in macrophages. Our findings establish HDAC6 as a protective regulator in atherosclerosis, which maintains lipid metabolic homeostasis by modulating the STAT3-CD36/SR-A axis. We also observed that systemic HDAC6 knockout exacerbated atherosclerotic progression in high-fat diet-fed ApoE Show less
📄 PDF DOI: 10.1038/s41419-025-08344-y
APOE
Meng-Ting Jiang, Shi-Lei Wan, Xiang-Yu Shen +4 more · 2025 · Journal of inflammation research · added 2026-04-24
Endothelial cells (ECs) senescence has emerged as a critical factor in the pathogenesis of atherosclerosis, contributing to vascular aging and plaque formation. However, the molecular mechanisms under Show more
Endothelial cells (ECs) senescence has emerged as a critical factor in the pathogenesis of atherosclerosis, contributing to vascular aging and plaque formation. However, the molecular mechanisms underlying endothelial senescence in atherosclerosis remain poorly understood. Single-cell RNA sequencing (scRNA-seq) data from atherosclerotic core plaques and adjacent normal tissues were analyzed using the Seurat package to identify cell subpopulations and senescence markers. RNA-seq data from early and late atherosclerotic plaques were used for differential gene expression analysis. Subsequently, the candidate gene was identified and validated in the atherosclerotic plaques of Single-cell analysis revealed elevated levels of senescence markers in ECs within atherosclerotic plaques. Combined with bulk RNA-seq analysis, This study highlights the critical role of endothelial senescence in atherosclerosis and identifies Show less
📄 PDF DOI: 10.2147/JIR.S544852
APOE
Anjing Liu, Roulan Jiang, Ruixi Li +16 more · 2025 · Research square · added 2026-04-24
Molecular QTL studies quantify whether genetic variants affect molecular traits, but non-linear effects including distributional patterns, variance, and interactions provide mechanistic insights beyon Show more
Molecular QTL studies quantify whether genetic variants affect molecular traits, but non-linear effects including distributional patterns, variance, and interactions provide mechanistic insights beyond mean-level associations. Methods for detecting distributional effects have been developed for eQTL analysis, yet applications have focused on method demonstrations rather than large-scale biological discovery. We comprehensively mapped quantile, variance, and interaction QTLs across 34 data-set from 22 molecular contexts in >2,300 human brain donors, revealing that 48.7% of quantile QTLs (qQTLs) exhibit context-dependent regulation invisible to linear models, with enrichment at phenotypic extremes and in cell-type-specific regulatory elements, chromatin accessibility regions, and long-range chromosomal contacts. qQTL variants explained additional trait heritability beyond linear QTLs for brain-related traits. At Alzheimer's disease (AD) risk loci, qQTL analysis revealed complex regulatory architecture including variance effects at Show less
📄 PDF DOI: 10.21203/rs.3.rs-8219833/v1
APOE
Yao Chen, Meiting Lu, Lu Zhang +9 more · 2025 · Drug delivery and translational research · Springer · added 2026-04-24
Atherosclerosis (AS), a chronic inflammatory disease linked to oxidative stress and lipid imbalance, remains a major cardiovascular threat. Traditional herbs Salvia miltiorrhiza and Carthamus tinctori Show more
Atherosclerosis (AS), a chronic inflammatory disease linked to oxidative stress and lipid imbalance, remains a major cardiovascular threat. Traditional herbs Salvia miltiorrhiza and Carthamus tinctorius exhibit multi-target anti-AS potential, yet their compositional complexity limits clinical translation. This study aimed to systematically identify core anti-AS components from these herbs and enhance their anti-AS efficacy via machine learning-aided screening and nanotechnology-driven codelivery. We initially pioneered a machine learning-aided hybrid strategy integrating network pharmacology and quantitative activity relationship (QSAR) modeling to identify four core anti-AS polyphenols (i.e., salvianic acid A, salvianolic acid B, protocatechuic acid, and hydroxysafflor yellow A). Subsequently, a quaternary metal-phenolic network (SSPH-MPN) was engineered for plaque-targeted codelivery, optimized via the median-effect principle for achieving a synergistic effect based on ROS scavenging efficacy. The optimized SSPH-MPN was characterized by a series of studies, including molecular dynamics simulations, UV, DLS, TEM, FTIR, XPS, and ICP-MS. The anti-AS effect of the optimized SSPH-MPN was evaluated by monitoring oxidative status (ROS levels, antioxidant enzymes SOD, GSH-Px, MDA, T-AOC), inflammatory markers (IL-1β, IL-6, TNF-α), lipid metabolism (DiI-oxLDL uptake, cholesterol efflux, blood lipid levels, lipid accumulation), and plaque areas. The results demonstrated that the optimized SSPH-MPN showed great efficiency in inhibiting lipid uptake and accumulation, and mediating cholesterol efflux in RAW 264.7 cells, and exhibited improved lipid metabolism, attenuated oxidative stress and inflammation, thus acquired diminished plaque area in apoE Show less
📄 PDF DOI: 10.1007/s13346-025-02023-3
APOE
Wei Li, Yu Cao, Chen Yu +5 more · 2025 · Frontiers in genetics · Frontiers · added 2026-04-24
Coronary heart disease (CHD) and type 2 diabetes (T2D) represent a significant global comorbidity burden, with shared yet incompletely understood molecular mechanisms. This study aimed to identify sha Show more
Coronary heart disease (CHD) and type 2 diabetes (T2D) represent a significant global comorbidity burden, with shared yet incompletely understood molecular mechanisms. This study aimed to identify shared diagnostic biomarkers and elucidate core pathways linking CHD and T2D pathogenesis. Integrated bioinformatics of CHD/T2D transcriptomes identified shared differentially expressed genes (DEGs) and co-expression modules via Weighted Gene Co-expression Network Analysis (WGCNA). Receiver operating characteristic (ROC) analysis selected CPD, GGCT, SUZ12, and ZMYM2 as top diagnostic biomarkers. These predictions were validated using C57BL/6 and ApoE Bioinformatics revealed 328 shared DEGs, with CPD, GGCT, SUZ12, and ZMYM2 showing high diagnostic efficacy. T2D mice exhibited persistent hyperglycemia. Aortic histopathology confirmed disease-specific changes: atherosclerotic plaques in CHD and vascular basement membrane thickening in T2D. Critically, all four biomarkers showed concurrent upregulation in diseased vessels at both protein (immunofluorescence, Western blot) and mRNA (RT-qPCR) levels. This study establishes CPD, GGCT, SUZ12, and ZMYM2 as shared CHD/T2D diagnostic biomarkers. Their validated co-upregulation highlights their dual-disease diagnostic and therapeutic potential. Show less
📄 PDF DOI: 10.3389/fgene.2025.1673303
APOE
Xiaoguang Li, Ning Dou, Linshan Zhong +5 more · 2025 · BME frontiers · added 2026-04-24
📄 PDF DOI: 10.34133/bmef.0203
APOE
Yuemei Zhang, Yuxin Cao, Yongxin Sun +12 more · 2025 · Proceedings of the National Academy of Sciences of the United States of America · National Academy of Sciences · added 2026-04-24
The activation of blood monocytes and the infiltration of monocyte-derived macrophages into the vessel walls are the central part of atherosclerosis. However, the mechanisms underlying the processes r Show more
The activation of blood monocytes and the infiltration of monocyte-derived macrophages into the vessel walls are the central part of atherosclerosis. However, the mechanisms underlying the processes remain unclear. Here, we report that G-protein signaling modulator 1 (GPSM1) plays a critical role in atherogenesis. We found that GPSM1 expression in lesional macrophages was increased during atherosclerosis development both in mice and humans. Myeloid-specific GPSM1 ablation protects mice against atherosclerosis and reduces aortic inflammation in both Show less
no PDF DOI: 10.1073/pnas.2517531122
APOE
Jinyu Bai, Xueli Qiu, Huajian Shan +10 more · 2025 · Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · Oxford University Press · added 2026-04-24
The Wnt/β-catenin signaling pathway is a classical pathway that regulates bone metabolism. The G protein inhibitory α subunits 1 and 3 (Gαi1/3) can couple with multiple growth factor/cytokine receptor Show more
The Wnt/β-catenin signaling pathway is a classical pathway that regulates bone metabolism. The G protein inhibitory α subunits 1 and 3 (Gαi1/3) can couple with multiple growth factor/cytokine receptors and act as universal adaptor proteins to mediate the activation of key downstream signaling pathways. However, it remains unclear whether and how Gαi1/3 proteins mediate Wnt/β-catenin signal transduction. In this study, we utilized single-cell sequencing analysis and employed viral transfection and gene editing techniques to alter the expression of Gαi1/3 in mouse embryonic osteoblast precursor cells. We examined the relationship between Gαi1/3 expression and the Wnt/β-catenin signaling pathway. Immunoprecipitation and confocal experiments were conducted to further explore the mechanisms by which Gαi1/3 exerts its functions. Osteogenic-related protein levels were detected by Western blotting, and the effects of Gαi1/3 proteins on osteogenic function were examined through alkaline phosphatase and Alizarin red staining. Additionally, micro-CT was used to compare bone mass in mice with different levels of Gαi1/3 expression, showing the relationship between Gαi1/3 and bone formation. Our findings indicate that Gαi1/3 proteins are significantly inversely correlated with age. Gαi1/3, rather than Gαi2, mediates the Wnt/β-catenin signaling pathway and promotes osteogenesis. Mechanistically, Gαi1/3 interacts with Axin1 and recruits it to the cell membrane, leading to inactivation of the β-catenin degradation complex. This results in β-catenin accumulation and nuclear translocation, where it activates the transcription of osteogenic genes. In vivo experiments further confirm that knockdown of Gαi1/3 significantly inhibits bone formation in mice. Our study identified Gαi1/3 as key regulatory proteins in Wnt/β-catenin signaling-mediated osteogenesis, and further elucidated its molecular mechanism in bone formation, which may provide a new therapeutic target for osteoporosis. Show less
no PDF DOI: 10.1093/jbmr/zjaf143
AXIN1
Zhaohan Li, Jun Yang, Jianan Li +10 more · 2025 · Translational neurodegeneration · BioMed Central · added 2026-04-24
The deposition of toxic aggregated amyloid-β (Aβ), resulting from continuous cleavage of amyloid precursor protein (APP) by β-site APP cleaving enzyme 1 (BACE1) and γ-secretase, is a key pathogenic ev Show more
The deposition of toxic aggregated amyloid-β (Aβ), resulting from continuous cleavage of amyloid precursor protein (APP) by β-site APP cleaving enzyme 1 (BACE1) and γ-secretase, is a key pathogenic event in Alzheimer's disease (AD). Small interfering RNAs (siRNA) have shown great potential for disease treatment by specifically silencing target genes. However, the poor brain delivery efficiency of siRNAs limits their therapeutic efficacy against AD. We designed a simplified and effective BACE1 siRNA (siBACE1) delivery system, namely, dendritic polyamidoamine modified with the neurotropic virus-derived peptide RVG29 and polyethylene glycol (PPR@siBACE1). PPR@siBACE1 crossed the blood-brain barrier efficiently and entered brain parenchyma in large amount, with subsequent neurotropism and potential microglia-targeting ability. Both in vitro and in vivo studies validated the effective brain delivery of siBACE1 and strong BACE1 silencing efficiency. Treatment of AD mice with PPR@siBACE1 inhibited the production of Aβ, potentiated Aβ phagocytosis by microglia, improved the memory deficits and reduced neuroinflammatory response in AD mice. This study provides a reliable delivery platform for gene therapies for AD. Show less
📄 PDF DOI: 10.1186/s40035-025-00503-7
BACE1
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