Chen Jian, Jian Dan, Bai Bingxue
Department of Dermatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China, 150086.
Clin Cosmet Investig Dermatol. 2025 Mar 13;18:567-577. doi: 10.2147/CCID.S484813. eCollection 2025.
Previous research has shown that metabolites (especially lipid-related metabolites) have a significant influence in the development of atopic dermatitis (AD). However, there is no evidence of a causal connection between metabolites and AD risk. The specific mechanisms require further elucidation. Our study employed a two-sample Mendelian randomization (TSMR) strategy to investigate how metabolite traits affect AD.
Utilizing publicly accessible GWAS data, we conducted TSMR studies to investigate the relationship between 233 metabolites traits (213 lipid-related traits and 20 no lipid-related traits) and AD. Our TSMR study primarily employed the Inverse-variance weighted method and four ancillary methods to analyze causation. Sensitivity analysis was performed to guarantee the TSMR results were trustworthy. Reverse MR analysis was used for investigating reverse causality.
After analyzing GWAS datasets for metabolites and AD, 13 metabolites were identified as positive. The MR analysis result indicates that total cholesterol in very small VLDL, cholesterol esters in very small VLDL, free cholesterol in IDL, concentration of medium LDL particles, concentration of large LDL particle, concentration of chylomicrons and extremely large VLDL particles, triglyceride levels in chylomicrons and extremely large VLDL, total lipid levels in chylomicrons and extremely large VLD, phospholipid levels in chylomicrons and extremely large VLDL, phospholipids in medium LDL, phospholipids in large LDL, phospholipids in small LDL, ratio of 18:2 linoleic acid to total fatty acids exhibited negative effects on AD. Reverse MR result analysis found that ratio of 18:2 linoleic acid to total fatty acids in serum was decreased in patients with AD. Sensitivity analyses ensure the stability of our results.
These findings highlight a definite correlation between metabolite and AD, demonstrating the significant role of 13 lipid-related metabolite traits. Our results significantly reduced the influence of unavoidable confounders and reverse causality. Our findings may set the framework for prospective therapeutic approaches and call for further investigation to validate them.
先前的研究表明，代谢物（尤其是脂质相关代谢物）在特应性皮炎（AD）的发病过程中具有显著影响。然而，尚无证据表明代谢物与AD风险之间存在因果关系。具体机制有待进一步阐明。我们的研究采用两样本孟德尔随机化（TSMR）策略来研究代谢物特征如何影响AD。
利用公开可得的全基因组关联研究（GWAS）数据，我们进行了TSMR研究，以调查233种代谢物特征（213种脂质相关特征和20种非脂质相关特征）与AD之间的关系。我们的TSMR研究主要采用逆方差加权法和四种辅助方法来分析因果关系。进行敏感性分析以确保TSMR结果可靠。采用反向MR分析来研究反向因果关系。
在分析了代谢物和AD的GWAS数据集后，确定了13种代谢物呈阳性。MR分析结果表明，极小微密度脂蛋白中的总胆固醇、极小微密度脂蛋白中的胆固醇酯、中间密度脂蛋白中的游离胆固醇、中等低密度脂蛋白颗粒浓度、大低密度脂蛋白颗粒浓度、乳糜微粒和极大极低密度脂蛋白颗粒浓度、乳糜微粒和极大极低密度脂蛋白中的甘油三酯水平、乳糜微粒和极大极低密度脂蛋白中的总脂质水平、乳糜微粒和极大极低密度脂蛋白中的磷脂水平、中等低密度脂蛋白中的磷脂、大低密度脂蛋白中的磷脂、小低密度脂蛋白中的磷脂、18:2亚油酸与总脂肪酸的比值对AD具有负面影响。反向MR结果分析发现，AD患者血清中18:2亚油酸与总脂肪酸的比值降低。敏感性分析确保了我们结果的稳定性。
这些发现突出了代谢物与AD之间的明确关联，证明了13种脂质相关代谢物特征的重要作用。我们的结果显著降低了不可避免的混杂因素和反向因果关系的影响。我们的发现可能为前瞻性治疗方法奠定框架，并呼吁进一步研究以验证它们。
