Xiaowen Hou, Jiaqi Zheng, Jiajun Zhang, Lin Tao, Kaiwen Cen, Ying Cui, Ji Wu
{"title":"评估低密度脂蛋白胆固醇水平对缺血性中风的因果效应:孟德尔随机研究","authors":"Xiaowen Hou, Jiaqi Zheng, Jiajun Zhang, Lin Tao, Kaiwen Cen, Ying Cui, Ji Wu","doi":"10.18502/ijph.v53i2.14924","DOIUrl":null,"url":null,"abstract":"Background: Ischemic stroke (IS) is the leading cause of disability and mortality worldwide. Low-density lipoprotein cholesterol (LDL-C) levels hadno potential risk on ischemic stroke. However, higher LDL-C levels were closely related to IS. Based on two antagonistic viewpoints, a Mendelian randomization (MR) study was designed to evaluate the causal effects of LDL-C levels on IS. \nMethods: Datasets of LDL-C levels and ischemic stroke were acquired from genome-wide association studies (GWAS). Weighted median method was conducted for main analysis, and MR-Egger and inverse-variance weighted (IVW) methods were performed for auxiliary analyses. Heterogeneity and pleiotropic tests were utilized to confirm the reliability of this study. \nResults: A total of 359 single nucleotide polymorphisms (SNPs) were associated with LDL-C levels (P < 5 × 10−8) and 337 SNPs were available in ischemic stroke with eliminating outliers. LDL-C levels were significantly associated with ischemic stroke (OR = 1.104, 95%CI = 1.019 - 1.195, P = 1.52 × 10-2). MR-Egger and IVW showed directionally similar estimates (MR-Egger: OR = 1.120, 95%CI = 1.040 - 1.207, P = 3.12 × 10-3; IVW: OR = 1.120, 95%CI = 1.064 - 1.178, P = 1.17 × 10-5). \nConclusion: LDL-C levels had causal effects on IS, providing insights into the design of future interventions to reduce the burden of ischemic stroke. \n ","PeriodicalId":510223,"journal":{"name":"Iranian Journal of Public Health","volume":"342 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating the Causal Effects of Low Density Lipoprotein Cholesterol Levels on Ischemic Stroke: A Mendelian Randomization Study\",\"authors\":\"Xiaowen Hou, Jiaqi Zheng, Jiajun Zhang, Lin Tao, Kaiwen Cen, Ying Cui, Ji Wu\",\"doi\":\"10.18502/ijph.v53i2.14924\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Ischemic stroke (IS) is the leading cause of disability and mortality worldwide. Low-density lipoprotein cholesterol (LDL-C) levels hadno potential risk on ischemic stroke. However, higher LDL-C levels were closely related to IS. Based on two antagonistic viewpoints, a Mendelian randomization (MR) study was designed to evaluate the causal effects of LDL-C levels on IS. \\nMethods: Datasets of LDL-C levels and ischemic stroke were acquired from genome-wide association studies (GWAS). Weighted median method was conducted for main analysis, and MR-Egger and inverse-variance weighted (IVW) methods were performed for auxiliary analyses. Heterogeneity and pleiotropic tests were utilized to confirm the reliability of this study. \\nResults: A total of 359 single nucleotide polymorphisms (SNPs) were associated with LDL-C levels (P < 5 × 10−8) and 337 SNPs were available in ischemic stroke with eliminating outliers. LDL-C levels were significantly associated with ischemic stroke (OR = 1.104, 95%CI = 1.019 - 1.195, P = 1.52 × 10-2). MR-Egger and IVW showed directionally similar estimates (MR-Egger: OR = 1.120, 95%CI = 1.040 - 1.207, P = 3.12 × 10-3; IVW: OR = 1.120, 95%CI = 1.064 - 1.178, P = 1.17 × 10-5). \\nConclusion: LDL-C levels had causal effects on IS, providing insights into the design of future interventions to reduce the burden of ischemic stroke. \\n \",\"PeriodicalId\":510223,\"journal\":{\"name\":\"Iranian Journal of Public Health\",\"volume\":\"342 \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Iranian Journal of Public Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18502/ijph.v53i2.14924\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Public Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18502/ijph.v53i2.14924","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluating the Causal Effects of Low Density Lipoprotein Cholesterol Levels on Ischemic Stroke: A Mendelian Randomization Study
Background: Ischemic stroke (IS) is the leading cause of disability and mortality worldwide. Low-density lipoprotein cholesterol (LDL-C) levels hadno potential risk on ischemic stroke. However, higher LDL-C levels were closely related to IS. Based on two antagonistic viewpoints, a Mendelian randomization (MR) study was designed to evaluate the causal effects of LDL-C levels on IS.
Methods: Datasets of LDL-C levels and ischemic stroke were acquired from genome-wide association studies (GWAS). Weighted median method was conducted for main analysis, and MR-Egger and inverse-variance weighted (IVW) methods were performed for auxiliary analyses. Heterogeneity and pleiotropic tests were utilized to confirm the reliability of this study.
Results: A total of 359 single nucleotide polymorphisms (SNPs) were associated with LDL-C levels (P < 5 × 10−8) and 337 SNPs were available in ischemic stroke with eliminating outliers. LDL-C levels were significantly associated with ischemic stroke (OR = 1.104, 95%CI = 1.019 - 1.195, P = 1.52 × 10-2). MR-Egger and IVW showed directionally similar estimates (MR-Egger: OR = 1.120, 95%CI = 1.040 - 1.207, P = 3.12 × 10-3; IVW: OR = 1.120, 95%CI = 1.064 - 1.178, P = 1.17 × 10-5).
Conclusion: LDL-C levels had causal effects on IS, providing insights into the design of future interventions to reduce the burden of ischemic stroke.