{"title":"缬氨酸对卵巢癌的因果效应:双向孟德尔随机化分析。","authors":"Xinyan Gao, Yanling Lin, Jun Zhang, Xiaoxiang Jiang, Riping Wu, Dongta Zhong","doi":"10.1080/01635581.2024.2445870","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Ovarian cancer is a lethal female cancer with a rising incidence that is often diagnosed late due to a lack of symptoms, affecting survival and quality of life. Studies suggest that dietary factors, especially the levels of branched-chain amino acids such as valine, may influence its development. While valine is essential for metabolism, its specific role in ovarian cancer remains unclear, necessitating further research.</p><p><strong>Methods: </strong>This study aimed to elucidate the causal relationship between valine and OC through a bidirectional Mendelian randomization (MR) approach. Data were sourced from the IEU OpenGWAS project, encompassing genome-wide association statistics for valine (<i>N</i> = 115,048) and OC (Ncase = 1,218, Ncontrol = 198,523) among European participants. Independent genetic variants associated with each phenotype at genome-wide significance were employed as instrumental variables (IVs). The primary analysis utilized the inverse variance weighted (IVW) method for two-sample MR analysis. MR‒Egger regression was applied to adjust for potential pleiotropy, whereas the weighted median method provided robust causal estimates under the assumption of valid IVs. Sensitivity analyses, including leave-one-out (LOO) analysis, heterogeneity tests, and horizontal pleiotropy assessments, were conducted to ensure the robustness of the findings.</p><p><strong>Results: </strong>The results revealed a significant causal relationship between valine and OC, identifying valine as a risk factor for OC (<i>p</i> = 0.043, 95% CI = 1.00008-1.00491, OR = 1.00249) in the forward MR analysis. Sensitivity analyses confirmed the absence of heterogeneity (Q_p value >0.05) and horizontal pleiotropy (<i>p</i> > 0.05), and LOO analysis validated the stability of the results. Conversely, reverse MR analysis revealed no causal effect of OC on valine levels (<i>p</i> = 0.875, 95% CI = 0.34125-2.51495, OR = 1.08528).</p><p><strong>Conclusions: </strong>These findings reveal a causal link between high valine levels and an increased OC risk. This research highlights the monitoring of valine levels as a preventive strategy and the significance of valine metabolism in OC. Future studies are needed to investigate the mechanisms and interventions for reducing risk, offering insights for clinical practice and public health initiatives in OC prevention.</p>","PeriodicalId":54701,"journal":{"name":"Nutrition and Cancer-An International Journal","volume":" ","pages":"405-413"},"PeriodicalIF":2.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Causal Effects of Valine on Ovarian Cancer: A Bidirectional Mendelian Randomization Analysis.\",\"authors\":\"Xinyan Gao, Yanling Lin, Jun Zhang, Xiaoxiang Jiang, Riping Wu, Dongta Zhong\",\"doi\":\"10.1080/01635581.2024.2445870\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Ovarian cancer is a lethal female cancer with a rising incidence that is often diagnosed late due to a lack of symptoms, affecting survival and quality of life. Studies suggest that dietary factors, especially the levels of branched-chain amino acids such as valine, may influence its development. While valine is essential for metabolism, its specific role in ovarian cancer remains unclear, necessitating further research.</p><p><strong>Methods: </strong>This study aimed to elucidate the causal relationship between valine and OC through a bidirectional Mendelian randomization (MR) approach. Data were sourced from the IEU OpenGWAS project, encompassing genome-wide association statistics for valine (<i>N</i> = 115,048) and OC (Ncase = 1,218, Ncontrol = 198,523) among European participants. Independent genetic variants associated with each phenotype at genome-wide significance were employed as instrumental variables (IVs). The primary analysis utilized the inverse variance weighted (IVW) method for two-sample MR analysis. MR‒Egger regression was applied to adjust for potential pleiotropy, whereas the weighted median method provided robust causal estimates under the assumption of valid IVs. Sensitivity analyses, including leave-one-out (LOO) analysis, heterogeneity tests, and horizontal pleiotropy assessments, were conducted to ensure the robustness of the findings.</p><p><strong>Results: </strong>The results revealed a significant causal relationship between valine and OC, identifying valine as a risk factor for OC (<i>p</i> = 0.043, 95% CI = 1.00008-1.00491, OR = 1.00249) in the forward MR analysis. Sensitivity analyses confirmed the absence of heterogeneity (Q_p value >0.05) and horizontal pleiotropy (<i>p</i> > 0.05), and LOO analysis validated the stability of the results. Conversely, reverse MR analysis revealed no causal effect of OC on valine levels (<i>p</i> = 0.875, 95% CI = 0.34125-2.51495, OR = 1.08528).</p><p><strong>Conclusions: </strong>These findings reveal a causal link between high valine levels and an increased OC risk. This research highlights the monitoring of valine levels as a preventive strategy and the significance of valine metabolism in OC. Future studies are needed to investigate the mechanisms and interventions for reducing risk, offering insights for clinical practice and public health initiatives in OC prevention.</p>\",\"PeriodicalId\":54701,\"journal\":{\"name\":\"Nutrition and Cancer-An International Journal\",\"volume\":\" \",\"pages\":\"405-413\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nutrition and Cancer-An International Journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/01635581.2024.2445870\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/2 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"NUTRITION & DIETETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nutrition and Cancer-An International Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/01635581.2024.2445870","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/2 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
引用次数: 0
摘要
背景:卵巢癌是一种发病率不断上升的致死性女性癌症,常因无症状而诊断较晚,影响生存和生活质量。研究表明,饮食因素,特别是支链氨基酸如缬氨酸的水平,可能会影响其发展。虽然缬氨酸对新陈代谢至关重要,但其在卵巢癌中的具体作用尚不清楚,需要进一步研究。方法:本研究旨在通过双向孟德尔随机化(MR)方法阐明缬氨酸与OC之间的因果关系。数据来自IEU OpenGWAS项目,包括欧洲参与者中缬氨酸(N = 115,048)和OC (N = 1,218, N = 198,523)的全基因组关联统计数据。在全基因组意义上与每种表型相关的独立遗传变异被用作工具变量(IVs)。初步分析采用反方差加权(IVW)方法进行双样本MR分析。采用MR-Egger回归来调整潜在的多效性,而加权中位数法在有效iv的假设下提供了稳健的因果估计。进行敏感性分析,包括遗漏(LOO)分析、异质性检验和水平多效性评估,以确保研究结果的稳健性。结果:结果显示缬氨酸与OC之间存在显著的因果关系,确定缬氨酸是OC的危险因素(p = 0.043, 95% CI = 1.00008-1.00491, OR = 1.00249)。敏感性分析证实不存在异质性(Q_p值>.05)和水平多效性(p >0.05), LOO分析验证了结果的稳定性。相反,反向MR分析显示OC对缬氨酸水平没有因果关系(p = 0.875, 95% CI = 0.34125-2.51495, OR = 1.08528)。结论:这些发现揭示了高缬氨酸水平与OC风险增加之间的因果关系。本研究强调了监测缬氨酸水平作为一种预防策略,以及缬氨酸代谢在OC中的意义。未来的研究需要探讨降低风险的机制和干预措施,为临床实践和公共卫生倡议提供见解。
Causal Effects of Valine on Ovarian Cancer: A Bidirectional Mendelian Randomization Analysis.
Background: Ovarian cancer is a lethal female cancer with a rising incidence that is often diagnosed late due to a lack of symptoms, affecting survival and quality of life. Studies suggest that dietary factors, especially the levels of branched-chain amino acids such as valine, may influence its development. While valine is essential for metabolism, its specific role in ovarian cancer remains unclear, necessitating further research.
Methods: This study aimed to elucidate the causal relationship between valine and OC through a bidirectional Mendelian randomization (MR) approach. Data were sourced from the IEU OpenGWAS project, encompassing genome-wide association statistics for valine (N = 115,048) and OC (Ncase = 1,218, Ncontrol = 198,523) among European participants. Independent genetic variants associated with each phenotype at genome-wide significance were employed as instrumental variables (IVs). The primary analysis utilized the inverse variance weighted (IVW) method for two-sample MR analysis. MR‒Egger regression was applied to adjust for potential pleiotropy, whereas the weighted median method provided robust causal estimates under the assumption of valid IVs. Sensitivity analyses, including leave-one-out (LOO) analysis, heterogeneity tests, and horizontal pleiotropy assessments, were conducted to ensure the robustness of the findings.
Results: The results revealed a significant causal relationship between valine and OC, identifying valine as a risk factor for OC (p = 0.043, 95% CI = 1.00008-1.00491, OR = 1.00249) in the forward MR analysis. Sensitivity analyses confirmed the absence of heterogeneity (Q_p value >0.05) and horizontal pleiotropy (p > 0.05), and LOO analysis validated the stability of the results. Conversely, reverse MR analysis revealed no causal effect of OC on valine levels (p = 0.875, 95% CI = 0.34125-2.51495, OR = 1.08528).
Conclusions: These findings reveal a causal link between high valine levels and an increased OC risk. This research highlights the monitoring of valine levels as a preventive strategy and the significance of valine metabolism in OC. Future studies are needed to investigate the mechanisms and interventions for reducing risk, offering insights for clinical practice and public health initiatives in OC prevention.
期刊介绍:
This timely publication reports and reviews current findings on the effects of nutrition on the etiology, therapy, and prevention of cancer. Etiological issues include clinical and experimental research in nutrition, carcinogenesis, epidemiology, biochemistry, and molecular biology. Coverage of therapy focuses on research in clinical nutrition and oncology, dietetics, and bioengineering. Prevention approaches include public health recommendations, preventative medicine, behavior modification, education, functional foods, and agricultural and food production policies.