Department of Health Statistics, School of Preventive Medicine, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Fourth Military Medical University, Xi'an, Shaanxi, China.
Department of Field and Disaster Nursing, Fourth Military Medical University, Xi'an, Shaanxi, China.
Front Immunol. 2024 Apr 15;15:1300457. doi: 10.3389/fimmu.2024.1300457. eCollection 2024.
Extensive evidence suggests a link between alterations in serum metabolite composition and various autoimmune diseases (ADs). Nevertheless, the causal relationship underlying these correlations and their potential utility as dependable biomarkers for early AD detection remain uncertain.
The objective of this study was to employ a two-sample Mendelian randomization (MR) approach to ascertain the causal relationship between serum metabolites and ADs. Additionally, a meta-analysis incorporating data from diverse samples was conducted to enhance the validation of this causal effect.
A two-sample MR analysis was performed to investigate the association between 486 human serum metabolites and six prevalent autoimmune diseases: systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), inflammatory bowel disease (IBD), dermatomyositis (DM), type 1 diabetes (T1D), and celiac disease (CeD). The inverse variance weighted (IVW) model was employed as the primary analytical technique for the two-sample MR analysis, aiming to identify blood metabolites linked with autoimmune diseases. Independent outcome samples were utilized for further validation of significant blood metabolites. Additional sensitivity analyses, including heterogeneity test, horizontal pleiotropy test, and retention rate analysis, were conducted. The results from these analyses were subsequently meta-integrated. Finally, metabolic pathway analysis was performed using the KEGG and Small Molecule Pathway Databases (SMPD).
Following the discovery and replication phases, eight metabolites were identified as causally associated with various autoimmune diseases, encompassing five lipid metabolism types: 1-oleoylglycerophosphoethanolamine, 1-arachidonoylglycerophosphoethanolamine, 1-myristoylglycerophosphocholine, arachidonate (20:4 n6), and glycerol. The meta-analysis indicated that three out of these eight metabolites exhibited a protective effect, while the remaining five were designated as pathogenic factors. The robustness of these associations was further confirmed through sensitivity analysis. Moreover, an investigation into metabolic pathways revealed a significant correlation between galactose metabolism and autoimmune diseases.
This study revealed a causal relationship between lipid metabolites and ADs, providing novel insights into the mechanism of AD development mediated by serum metabolites and possible biomarkers for early diagnosis.
大量证据表明，血清代谢物组成的改变与各种自身免疫性疾病（AD）之间存在关联。然而，这些相关性背后的因果关系及其作为 AD 早期检测可靠生物标志物的潜在效用仍不确定。
本研究采用两样本 Mendelian 随机化（MR）方法，确定血清代谢物与 AD 之间的因果关系。此外，还进行了一项包含来自不同样本数据的荟萃分析，以增强该因果效应的验证。
进行了两样本 MR 分析，以研究 486 个人类血清代谢物与六种常见自身免疫性疾病（系统性红斑狼疮（SLE）、类风湿关节炎（RA）、炎症性肠病（IBD）、皮肌炎（DM）、1 型糖尿病（T1D）和乳糜泻（CeD））之间的关联。作为两样本 MR 分析的主要分析技术，采用了逆方差加权（IVW）模型，旨在确定与自身免疫性疾病相关的血液代谢物。使用独立的结果样本进一步验证有意义的血液代谢物。还进行了额外的敏感性分析，包括异质性检验、水平多效性检验和保留率分析。随后对这些分析的结果进行了荟萃分析。最后，使用 KEGG 和小分子途径数据库（SMPD）进行代谢途径分析。
在发现和复制阶段之后，确定了八种代谢物与各种自身免疫性疾病有因果关系，包括五种脂质代谢类型：1-油酰基甘油磷酸乙醇胺、1-花生四烯酰基甘油磷酸乙醇胺、1-肉豆蔻酰基甘油磷酸胆碱、花生四烯酸（20:4 n6）和甘油。荟萃分析表明，这八种代谢物中有三种具有保护作用，而其余五种则被指定为致病因素。通过敏感性分析进一步证实了这些关联的稳健性。此外，对代谢途径的研究表明，半乳糖代谢与自身免疫性疾病之间存在显著相关性。
本研究揭示了脂质代谢物与 AD 之间的因果关系，为血清代谢物介导的 AD 发病机制提供了新的见解，并为 AD 的早期诊断提供了可能的生物标志物。
