评估 1,400 种血液代谢物与重度抑郁障碍的关系:孟德尔随机研究

Tiantian Dong, Xingxin Wang, Zhixia Jia, Jiguo Yang, Yuanxiang Liu
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引用次数: 0

摘要

重度抑郁症(MDD)是全球最普遍、最令人沮丧的健康问题之一。以前的研究曾报道过代谢失调与 MDD 之间的联系。利用双样本双向孟德尔随机分析法(MR),我们评估了 1400 种血清代谢物与重度抑郁症(MDD)之间的因果关系。我们采用了反方差加权法(IVW)来估计暴露与结果之间的因果关系。此外,还采用了MR-Egger回归法、加权中值法、简单模式法和加权模式法作为补充方法,以全面评估血液代谢物与MDD之间的因果关系。此外,还进行了多向性和异质性检验。最后,我们对相关代谢物进行了代谢物功能分析,并采用反向 MR 方法探讨了 MDD 对这些代谢物的潜在影响。在所有代谢物中,33 种代谢物与 MDD 呈正相关,32 种代谢物与 MDD 呈负相关。增加患重度抑郁症风险的前五种代谢物是花生四烯酸(20:4n6)与亚油酸(18:2n6)的比率、LysoPE(18:0/0:0)、N-乙酰-beta-丙氨酸水平、花生四烯酸(20:4n6)与油酸和疫苗酸(18:1)的比率、谷氨酰胺酰谷氨酰胺和苏氨酸与丙酮酸的比率。相反,降低 MDD 风险的前五种代谢物是 N6-乙酰基-L-赖氨酸、油酰-亚油酰-甘油(18:1 至 18:2) [2] 与亚油酰-丙烯酰-甘油(18:2 至 20:4) [2] 的比率、蛋氨酸与磷酸盐的比率、孕烷二醇 3-O-葡萄糖醛酸和 6-氧代哌啶-2-羧酸。代谢物功能富集主要集中在胆汁酸生物合成(FDR=0.177)、谷胱甘肽代谢(FDR=0.177)、苏氨酸和 2-氧代丁酸降解(FDR=0.177)等途径。此外,缬氨酸、亮氨酸和异亮氨酸的生物合成(P=0.04)以及抗坏血酸和醛酸代谢(P=0.04)等通路也出现了富集。此外,我们还筛选出了三个功能富集组和两条代谢途径。基因组学与代谢组学的结合为MDD的筛查和预防提供了重要启示。
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Assessing the associations of 1,400 blood metabolites with major depressive disorder: a Mendelian randomization study
Major Depressive Disorder (MDD) is one of the most prevalent and debilitating health conditions worldwide. Previous studies have reported a link between metabolic dysregulation and MDD. However, evidence for a causal relationship between blood metabolites and MDD is lacking.Using a two-sample bidirectional Mendelian randomization analysis (MR), we assessed the causal relationship between 1,400 serum metabolites and Major Depressive Disorder (MDD). The Inverse Variance Weighted method (IVW) was employed to estimate the causal association between exposures and outcomes. Additionally, MR-Egger regression, weighted median, simple mode, and weighted mode methods were used as supplementary approaches for a comprehensive appraisal of the causality between blood metabolites and MDD. Pleiotropy and heterogeneity tests were also conducted. Lastly, the relevant metabolites were subjected to metabolite function analysis, and a reverse MR was implemented to explore the potential influence of MDD on these metabolites.After rigorous screening, we identified 34 known metabolites, 13 unknown metabolites, and 18 metabolite ratios associated with Major Depressive Disorder (MDD). Among all metabolites, 33 were found to have positive associations, and 32 had negative associations. The top five metabolites that increased the risk of MDD were the Arachidonate (20:4n6) to linoleate (18:2n6) ratio, LysoPE(18:0/0:0), N-acetyl-beta-alanine levels, Arachidonate (20:4n6) to oleate to vaccenate (18:1) ratio, Glutaminylglutamine, and Threonine to pyruvate ratio. Conversely, the top five metabolites that decreased the risk of MDD were N6-Acetyl-L-lysine, Oleoyl-linoleoyl-glycerol (18:1 to 18:2) [2] to linoleoyl-arachidonoyl-glycerol (18:2 to 20:4) [2] ratio, Methionine to phosphate ratio, Pregnanediol 3-O-glucuronide, and 6-Oxopiperidine-2-carboxylic acid. Metabolite function enrichment was primarily concentrated in pathways such as Bile Acid Biosynthesis (FDR=0.177), Glutathione Metabolism (FDR=0.177), Threonine, and 2-Oxobutanoate Degradation (FDR=0.177). In addition, enrichment was noted in pathways like Valine, Leucine, and Isoleucine Biosynthesis (p=0.04), as well as Ascorbate and Aldarate Metabolism (p=0.04).Within a pool of 1,400 blood metabolites, we identified 34 known metabolites and 13 unknown metabolites, as well as 18 metabolite ratios associated with Major Depressive Disorder (MDD). Additionally, three functionally enriched groups and two metabolic pathways were selected. The integration of genomics and metabolomics has provided significant insights for the screening and prevention of MDD.
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