{"title":"血浆代谢景观揭示白血病亚型进展的关键调节因子。","authors":"Cong Liang, Jia-Yu Lin, Liu-Hua Liao, Shi-Yao Song, Jia-Tong Dai, Jia-Jie Chen, Zhi-Yong Ke, Hong-Man Xue","doi":"10.1080/20565623.2025.2527015","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Leukemia is driven by metabolic reprogramming, yet the specific causal roles of plasma metabolites in distinct leukemia subtypes remain unclear.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":12568,"journal":{"name":"Future Science OA","volume":"11 1","pages":"2527015"},"PeriodicalIF":2.1000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12407637/pdf/","citationCount":"0","resultStr":"{\"title\":\"Plasma metabolic landscape unveils key regulators of leukemia subtype progression.\",\"authors\":\"Cong Liang, Jia-Yu Lin, Liu-Hua Liao, Shi-Yao Song, Jia-Tong Dai, Jia-Jie Chen, Zhi-Yong Ke, Hong-Man Xue\",\"doi\":\"10.1080/20565623.2025.2527015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Leukemia is driven by metabolic reprogramming, yet the specific causal roles of plasma metabolites in distinct leukemia subtypes remain unclear.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":12568,\"journal\":{\"name\":\"Future Science OA\",\"volume\":\"11 1\",\"pages\":\"2527015\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12407637/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Future Science OA\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/20565623.2025.2527015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/9/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Science OA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/20565623.2025.2527015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/9/1 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Plasma metabolic landscape unveils key regulators of leukemia subtype progression.
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.
期刊介绍:
Future Science OA is an online, open access, peer-reviewed title from the Future Science Group. The journal covers research and discussion related to advances in biotechnology, medicine and health. The journal embraces the importance of publishing all good-quality research with the potential to further the progress of research in these fields. All original research articles will be considered that are within the journal''s scope, and have been conducted with scientific rigour and research integrity. The journal also features review articles, editorials and perspectives, providing readers with a leading source of commentary and analysis. Submissions of the following article types will be considered: -Research articles -Preliminary communications -Short communications -Methodologies -Trial design articles -Trial results (including early-phase and negative studies) -Reviews -Perspectives -Commentaries