Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, 225009, China.
Jiangsu Key Laboratory of Integrated Traditional Chinese and Western Medicine for Prevention and Treatment of Senile Diseases, Yangzhou University, Yangzhou, 225009, China.
Sci Rep. 2023 Nov 1;13(1):18818. doi: 10.1038/s41598-023-45801-0.
Previous studies have shown that metabolites play an important role in phenotypic regulation. However, the causal relationship between metabolites and multiple myeloma has not been adequately investigated. Here, we attempt to explore the causal effects of genetically determined blood metabolites on multiple myeloma. The large-scale public blood metabolites and multiple myeloma datasets from independently published genome-wide association studies (GWAS) were used to explore the causal relationship between each genetically determined blood metabolite and multiple myeloma through inverse variance weighted (IVW), weighted median, MR-Egger and mode-based estimation methods. Sensitivity tests were performed to evaluate the stability and reliability of the results by MR-Egger regression and leave-one-out methods. Metabolic pathway analysis was further explored using filtered data. Statistical analyses were all performed in R. Among 452 metabolites, ten known metabolites and three unknown metabolites had significant causal relationship with multiple myeloma (P < 0.05). Four known metabolites, 3-methyl-2-oxovalenate, oxidized bilirubin, isovalerylcarnitine and glutamine carnitine, reached statistical significance in IVW models. Metabolic pathways analysis identified four significant pathways. The occurrence of multiple myeloma may have a causal relationship with these four metabolites, and there are four metabolic pathways that are also related to the occurrence of multiple myeloma. This can provide new ideas for exploring early screening and treatment of multiple myeloma.
先前的研究表明，代谢物在表型调控中起着重要作用。然而，代谢物与多发性骨髓瘤之间的因果关系尚未得到充分研究。在这里，我们试图探讨遗传决定的血液代谢物对多发性骨髓瘤的因果影响。使用来自独立发表的全基因组关联研究（GWAS）的大规模公共血液代谢物和多发性骨髓瘤数据集，通过逆方差加权（IVW）、加权中位数、MR-Egger 和基于模式的估计方法，探索每种遗传决定的血液代谢物与多发性骨髓瘤之间的因果关系。通过 MR-Egger 回归和逐一剔除方法进行敏感性测试，以评估结果的稳定性和可靠性。进一步使用过滤数据进行代谢途径分析。所有统计分析均在 R 中进行。在 452 种代谢物中，有 10 种已知代谢物和 3 种未知代谢物与多发性骨髓瘤有显著的因果关系（P<0.05）。在 IVW 模型中，有 4 种已知代谢物（3-甲基-2-氧代戊酸、氧化胆红素、异戊酰肉碱和谷氨酰胺肉碱）达到了统计学意义。代谢途径分析确定了四个显著的途径。多发性骨髓瘤的发生可能与这四种代谢物有因果关系，并且有四个代谢途径也与多发性骨髓瘤的发生有关。这可以为探索多发性骨髓瘤的早期筛查和治疗提供新的思路。
