{"title":"基因决定的血浆代谢物与类风湿关节炎之间的因果关系。","authors":"Kunpeng Song, Julei Ma, Bing Wang","doi":"10.1111/1756-185X.15447","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Presently, research examining the impact of plasma metabolites on rheumatoid arthritis (RA) is scarce. We utilized a bidirectional two-sample Mendelian randomization (MR) analysis to explore the potential causal link between 1400 plasma metabolites and RA.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We performed a two-sample MR analysis to assess the causal association between 1400 plasma metabolites and RA. The primary method of two-sample MR Analysis was the Inverse Variance Weighted (IVW) model, and the secondary methods were the Weighted Median (WM) and MR Egger methods. We conducted sensitivity analyses using Cochran's <i>Q</i> test, MR-Egger intercept test, MR-PRESSO, and Leave-One-Out analyses. Steiger test was used for validation of the metabolites. The main results were validated in the UK Biobank.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>In the discovery dataset, 60 metabolites were identified as significantly associated with the onset of RA. A notable finding was the strong correlation between Valve levels and RA risk, showing the highest positive correlation (OR [95% CI]: 1.361 (1.112, 1.667), <i>p</i> = 0.0028). Subsequent analysis of the validation dataset revealed 46 metabolites linked to RA, with X-22771 levels displaying the strongest positive association (OR [95% CI]: 1.002 (1.00, 1.004), <i>p</i> = 0.037). Notably, Glycohydrocolate levels exhibited a protective effect on RA in both datasets. Specifically, the effect size in the initial dataset was (OR [95% CI]:0.867 (0.753, 1.000), <i>p</i> = 0.050), whereas in the validation dataset, the effect was weaker (OR [95% CI]: 0.999 (0.997, 1.000), <i>p</i> = 0.048). These findings were further validated through a series of sensitivity analyses, affirming their robustness and reliability.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>This study highlights a strong correlation between elevated Valine levels and an increased risk of RA, as well as potential protective effects of Glycohydrohorate in independent datasets.</p>\n </section>\n </div>","PeriodicalId":14330,"journal":{"name":"International Journal of Rheumatic Diseases","volume":"27 12","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Causal Relationship Between Genetically Determined Plasma Metabolites and Rheumatoid Arthritis\",\"authors\":\"Kunpeng Song, Julei Ma, Bing Wang\",\"doi\":\"10.1111/1756-185X.15447\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Presently, research examining the impact of plasma metabolites on rheumatoid arthritis (RA) is scarce. We utilized a bidirectional two-sample Mendelian randomization (MR) analysis to explore the potential causal link between 1400 plasma metabolites and RA.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We performed a two-sample MR analysis to assess the causal association between 1400 plasma metabolites and RA. The primary method of two-sample MR Analysis was the Inverse Variance Weighted (IVW) model, and the secondary methods were the Weighted Median (WM) and MR Egger methods. We conducted sensitivity analyses using Cochran's <i>Q</i> test, MR-Egger intercept test, MR-PRESSO, and Leave-One-Out analyses. Steiger test was used for validation of the metabolites. The main results were validated in the UK Biobank.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>In the discovery dataset, 60 metabolites were identified as significantly associated with the onset of RA. A notable finding was the strong correlation between Valve levels and RA risk, showing the highest positive correlation (OR [95% CI]: 1.361 (1.112, 1.667), <i>p</i> = 0.0028). Subsequent analysis of the validation dataset revealed 46 metabolites linked to RA, with X-22771 levels displaying the strongest positive association (OR [95% CI]: 1.002 (1.00, 1.004), <i>p</i> = 0.037). Notably, Glycohydrocolate levels exhibited a protective effect on RA in both datasets. Specifically, the effect size in the initial dataset was (OR [95% CI]:0.867 (0.753, 1.000), <i>p</i> = 0.050), whereas in the validation dataset, the effect was weaker (OR [95% CI]: 0.999 (0.997, 1.000), <i>p</i> = 0.048). 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引用次数: 0
摘要
背景:目前,关于血浆代谢物对类风湿关节炎(RA)影响的研究很少。我们利用双向双样本孟德尔随机化(MR)分析来探索1400种血浆代谢物与类风湿关节炎之间的潜在因果关系。方法:我们进行了两个样本的MR分析,以评估1400种血浆代谢物与RA之间的因果关系。双样本MR分析的主要方法是方差反加权(IVW)模型,次要方法是加权中位数(WM)和MR Egger方法。我们使用Cochran’s Q检验、MR-Egger截距检验、MR-PRESSO和Leave-One-Out分析进行敏感性分析。使用Steiger试验对代谢物进行验证。主要结果在英国生物银行得到了验证。结果:在发现数据集中,60种代谢物被确定为与RA的发病显著相关。一个值得注意的发现是瓣膜水平与RA风险之间有很强的相关性,显示出最高的正相关性(OR [95% CI]: 1.361 (1.112, 1.667), p = 0.0028)。随后对验证数据集的分析显示,46种代谢物与RA相关,其中X-22771水平显示出最强的正相关(OR [95% CI]: 1.002 (1.00, 1.004), p = 0.037)。值得注意的是,在两个数据集中,糖水合酸水平都显示出对RA的保护作用。具体来说,初始数据集中的效应大小为(OR [95% CI]:0.867 (0.753, 1.000), p = 0.050),而在验证数据集中,效应较弱(OR [95% CI]: 0.999 (0.997, 1.000), p = 0.048)。通过一系列敏感性分析进一步验证了这些发现,确认了其稳健性和可靠性。结论:本研究在独立数据集中强调缬氨酸水平升高与RA风险增加之间存在很强的相关性,以及氢糖酸盐的潜在保护作用。
The Causal Relationship Between Genetically Determined Plasma Metabolites and Rheumatoid Arthritis
Background
Presently, research examining the impact of plasma metabolites on rheumatoid arthritis (RA) is scarce. We utilized a bidirectional two-sample Mendelian randomization (MR) analysis to explore the potential causal link between 1400 plasma metabolites and RA.
Methods
We performed a two-sample MR analysis to assess the causal association between 1400 plasma metabolites and RA. The primary method of two-sample MR Analysis was the Inverse Variance Weighted (IVW) model, and the secondary methods were the Weighted Median (WM) and MR Egger methods. We conducted sensitivity analyses using Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and Leave-One-Out analyses. Steiger test was used for validation of the metabolites. The main results were validated in the UK Biobank.
Results
In the discovery dataset, 60 metabolites were identified as significantly associated with the onset of RA. A notable finding was the strong correlation between Valve levels and RA risk, showing the highest positive correlation (OR [95% CI]: 1.361 (1.112, 1.667), p = 0.0028). Subsequent analysis of the validation dataset revealed 46 metabolites linked to RA, with X-22771 levels displaying the strongest positive association (OR [95% CI]: 1.002 (1.00, 1.004), p = 0.037). Notably, Glycohydrocolate levels exhibited a protective effect on RA in both datasets. Specifically, the effect size in the initial dataset was (OR [95% CI]:0.867 (0.753, 1.000), p = 0.050), whereas in the validation dataset, the effect was weaker (OR [95% CI]: 0.999 (0.997, 1.000), p = 0.048). These findings were further validated through a series of sensitivity analyses, affirming their robustness and reliability.
Conclusions
This study highlights a strong correlation between elevated Valine levels and an increased risk of RA, as well as potential protective effects of Glycohydrohorate in independent datasets.
期刊介绍:
The International Journal of Rheumatic Diseases (formerly APLAR Journal of Rheumatology) is the official journal of the Asia Pacific League of Associations for Rheumatology. The Journal accepts original articles on clinical or experimental research pertinent to the rheumatic diseases, work on connective tissue diseases and other immune and allergic disorders. The acceptance criteria for all papers are the quality and originality of the research and its significance to our readership. Except where otherwise stated, manuscripts are peer reviewed by two anonymous reviewers and the Editor.