血浆代谢图谱揭示白血病亚型进展的关键调节因子。

Plasma metabolic landscape unveils key regulators of leukemia subtype progression.

作者信息

Liang Cong, Lin Jia-Yu, Liao Liu-Hua, Song Shi-Yao, Dai Jia-Tong, Chen Jia-Jie, Ke Zhi-Yong, Xue Hong-Man

机构信息

Department of Pediatrics, the Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.

Department of Pediatrics, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

出版信息

Future Sci OA. 2025 Dec;11(1):2527015. doi: 10.1080/20565623.2025.2527015. Epub 2025 Sep 1.

Abstract

BACKGROUND

Leukemia is driven by metabolic reprogramming, yet the specific causal roles of plasma metabolites in distinct leukemia subtypes remain unclear.

METHODS

This study employed Mendelian randomization (MR) to explore potential causal links between 690 plasma metabolites (and 143 metabolite ratios) and four leukemia subtypes: ALL, AML, CLL, and CML. Genetic variants from genome-wide association studies served as instrumental variables. Multiple MR approaches, including IVW, MR-Egger, and Weighted Median, along with sensitivity analyses, were applied to ensure robust results.

RESULTS

Our findings revealed subtype-specific metabolite associations. In ALL, metabolites such as 3-Hydroxyisobutyrate and γ-Glutamylglutamate showed positive associations, while Phosphocholine and Ceramide showed negative associations. AML was positively linked to GlcNAc/GalNAc and negatively to 1-Methylnicotinamide. CLL showed positive associations with Butyrate/Isobutyrate and Androstenediol Monosulfate, and negative ones with Docosatrienoate and α-Tocopherol to Sulfate ratio. CML exhibited negative associations with Cysteine-Glutathione disulfide and Piperine.

CONCLUSION

Our MR study provides a comprehensive evaluation of the metabolomic landscape of leukemia, identifying subtype-specific causal associations involving pathways such as energy metabolism, amino acid metabolism, lipid signaling, and redox homeostasis. These findings offer insights into potential plasma biomarkers and therapeutic targets, revealing distinct metabolic vulnerabilities that warrant further investigation for precision treatment strategies across leukemia subtypes.

摘要

背景

白血病由代谢重编程驱动,但血浆代谢物在不同白血病亚型中的具体因果作用仍不清楚。

方法

本研究采用孟德尔随机化(MR)方法,探讨690种血浆代谢物(及143种代谢物比值)与四种白血病亚型(急性淋巴细胞白血病、急性髓系白血病、慢性淋巴细胞白血病和慢性髓系白血病)之间的潜在因果联系。全基因组关联研究中的基因变异用作工具变量。应用了多种MR方法,包括逆方差加权法、MR-Egger回归法和加权中位数法,以及敏感性分析,以确保结果的稳健性。

结果

我们的研究结果揭示了亚型特异性的代谢物关联。在急性淋巴细胞白血病中,3-羟基异丁酸和γ-谷氨酰谷氨酸等代谢物呈正相关,而磷酸胆碱和神经酰胺呈负相关。急性髓系白血病与N-乙酰葡糖胺/ N-乙酰半乳糖胺呈正相关,与1-甲基烟酰胺呈负相关。慢性淋巴细胞白血病与丁酸/异丁酸和硫酸雄烯二醇单硫酸酯呈正相关,与二十二碳三烯酸和α-生育酚与硫酸盐的比值呈负相关。慢性髓系白血病与半胱氨酸-谷胱甘肽二硫化物和胡椒碱呈负相关。

结论

我们的MR研究对白血病的代谢组学特征进行了全面评估,确定了涉及能量代谢、氨基酸代谢、脂质信号传导和氧化还原稳态等途径的亚型特异性因果关联。这些发现为潜在的血浆生物标志物和治疗靶点提供了见解,揭示了不同的代谢脆弱性,值得进一步研究以制定针对白血病亚型的精准治疗策略。

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