{"title":"揭示烟雾病的血脂异常景观：OxLDL是一个关键的生物标志物","authors":"Chaofan Zeng, Haoyuan Chen, Jie Liu, Youyuan Bao, Xudong Sun, Fanbo Meng, Yimeng Xue, Yunhao Cui, Qianjun Zhao, Jing Zhang, Hao Li, Dong Zhang, Rong Wang, Yan Zhang, Guojun Zhang, Jizong Zhao, Qian Zhang","doi":"10.1111/cns.70441","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Aims</h3>\n \n <p>The pathogenic mechanisms of moyamoya disease (MMD) remain unrecognized. Although genetic predisposition and hemodynamic changes have been focused on, emerging evidence suggests dyslipidemia may also contribute to MMD. Here, we performed a comprehensive analysis of lipid profiles, aiming to elucidate potential mechanisms in MMD.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>In this prospective case–control study, 222 MMD patients and 231 healthy controls (HCs) were enrolled. The comprehensive lipid profiling was performed, encompassing standard lipids, apolipoproteins, oxidized low-density lipoprotein (oxLDL), and small dense LDL (sdLDL). Statistical models of weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) were applied to capture individual and joint lipid effects on MMD risk.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Compared with HCs, MMD patients exhibited significantly higher oxLDL, sdLDL, and lipoprotein(a) (<i>p</i> < 0.05). OxLDL emerged as a robust independent risk factor for MMD (adjusted OR 1.146, 95% CI 1.102–1.210, <i>p</i> < 0.001). WQS analysis further identified oxLDL as the single greatest contributor to MMD risk, with additional support from BKMR showing marked synergistic interactions between oxLDL and homocysteine.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>The study revealed a comprehensive dyslipidemic landscape in MMD, highlighting oxLDL as a pivotal biomarker. The results underscored the significance of lipid metabolism in MMD pathogenesis, warranting further investigation to guide novel diagnostic and therapeutic strategies.</p>\n </section>\n </div>","PeriodicalId":154,"journal":{"name":"CNS Neuroscience & Therapeutics","volume":"31 5","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cns.70441","citationCount":"0","resultStr":"{\"title\":\"Unraveling the Dyslipidemic Landscape in Moyamoya Disease: OxLDL as a Key Biomarker\",\"authors\":\"Chaofan Zeng, Haoyuan Chen, Jie Liu, Youyuan Bao, Xudong Sun, Fanbo Meng, Yimeng Xue, Yunhao Cui, Qianjun Zhao, Jing Zhang, Hao Li, Dong Zhang, Rong Wang, Yan Zhang, Guojun Zhang, Jizong Zhao, Qian Zhang\",\"doi\":\"10.1111/cns.70441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Aims</h3>\\n \\n <p>The pathogenic mechanisms of moyamoya disease (MMD) remain unrecognized. Although genetic predisposition and hemodynamic changes have been focused on, emerging evidence suggests dyslipidemia may also contribute to MMD. Here, we performed a comprehensive analysis of lipid profiles, aiming to elucidate potential mechanisms in MMD.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>In this prospective case–control study, 222 MMD patients and 231 healthy controls (HCs) were enrolled. The comprehensive lipid profiling was performed, encompassing standard lipids, apolipoproteins, oxidized low-density lipoprotein (oxLDL), and small dense LDL (sdLDL). Statistical models of weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) were applied to capture individual and joint lipid effects on MMD risk.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Compared with HCs, MMD patients exhibited significantly higher oxLDL, sdLDL, and lipoprotein(a) (<i>p</i> < 0.05). OxLDL emerged as a robust independent risk factor for MMD (adjusted OR 1.146, 95% CI 1.102–1.210, <i>p</i> < 0.001). WQS analysis further identified oxLDL as the single greatest contributor to MMD risk, with additional support from BKMR showing marked synergistic interactions between oxLDL and homocysteine.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>The study revealed a comprehensive dyslipidemic landscape in MMD, highlighting oxLDL as a pivotal biomarker. The results underscored the significance of lipid metabolism in MMD pathogenesis, warranting further investigation to guide novel diagnostic and therapeutic strategies.</p>\\n </section>\\n </div>\",\"PeriodicalId\":154,\"journal\":{\"name\":\"CNS Neuroscience & Therapeutics\",\"volume\":\"31 5\",\"pages\":\"\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2025-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cns.70441\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CNS Neuroscience & Therapeutics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/cns.70441\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CNS Neuroscience & Therapeutics","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/cns.70441","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Unraveling the Dyslipidemic Landscape in Moyamoya Disease: OxLDL as a Key Biomarker
Aims
The pathogenic mechanisms of moyamoya disease (MMD) remain unrecognized. Although genetic predisposition and hemodynamic changes have been focused on, emerging evidence suggests dyslipidemia may also contribute to MMD. Here, we performed a comprehensive analysis of lipid profiles, aiming to elucidate potential mechanisms in MMD.
Methods
In this prospective case–control study, 222 MMD patients and 231 healthy controls (HCs) were enrolled. The comprehensive lipid profiling was performed, encompassing standard lipids, apolipoproteins, oxidized low-density lipoprotein (oxLDL), and small dense LDL (sdLDL). Statistical models of weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) were applied to capture individual and joint lipid effects on MMD risk.
Results
Compared with HCs, MMD patients exhibited significantly higher oxLDL, sdLDL, and lipoprotein(a) (p < 0.05). OxLDL emerged as a robust independent risk factor for MMD (adjusted OR 1.146, 95% CI 1.102–1.210, p < 0.001). WQS analysis further identified oxLDL as the single greatest contributor to MMD risk, with additional support from BKMR showing marked synergistic interactions between oxLDL and homocysteine.
Conclusions
The study revealed a comprehensive dyslipidemic landscape in MMD, highlighting oxLDL as a pivotal biomarker. The results underscored the significance of lipid metabolism in MMD pathogenesis, warranting further investigation to guide novel diagnostic and therapeutic strategies.
期刊介绍：
CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews and reports of novel findings of therapeutic relevance to the central nervous system, as well as papers related to clinical pharmacology, drug development and novel methodologies for drug evaluation. The journal focuses on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.
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