Jiaqi Huang, Hadijah Nabalende, M Constanza Camargo, Jacqueline Lovett, Isaac Otim, Ismail D Legason, Martin D Ogwang, Patrick Kerchan, Tobias Kinyera, Leona W Ayers, Kishor Bhatia, James J Goedert, Steven J Reynolds, Peter D Crompton, Steven C Moore, Ruin Moaddel, Demetrius Albanes, Sam M Mbulaiteye
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The metabolomic patterns of BL is unknown.</p><p><strong>Materials and methods: </strong>We measured 627 metabolites in pre-chemotherapy treatment plasma samples from 25 male children (6-11 years) with BL and 25 cancer-free area- and age-frequency-matched male controls from the Epidemiology of Burkitt Lymphoma in East African Children and Minors study in Uganda using liquid chromatography-tandem mass spectrometry. Unconditional, age-adjusted logistic regression analysis was used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) for the BL association with 1-standard deviation increase in the log-metabolite concentration, adjusting for multiple comparisons using false discovery rate (FDR) thresholds and Bonferroni correction.</p><p><strong>Results: </strong>Compared to controls, levels for 42 metabolite concentrations differed in BL cases (FDR < 0.001), including triacylglyceride (18:0_38:6), alpha-aminobutyric acid (AABA), ceramide (d18:1/20:0), phosphatidylcholine ae C40:6 and phosphatidylcholine C38:6 as the top signals associated with BL (ORs = 6.9 to 14.7, P < 2.4✕10<sup>- 4</sup>). Two metabolites (triacylglyceride (18:0_38:6) and AABA) selected using stepwise logistic regression discriminated BL cases from controls with an area under the curve of 0.97 (95% CI: 0.94, 1.00).</p><p><strong>Conclusion: </strong>Our findings warrant further examination of plasma metabolites as potential biomarkers for BL risk/diagnosis.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11213758/pdf/","citationCount":"0","resultStr":"{\"title\":\"Plasma metabolites in childhood Burkitt lymphoma cases and cancer-free controls in Uganda.\",\"authors\":\"Jiaqi Huang, Hadijah Nabalende, M Constanza Camargo, Jacqueline Lovett, Isaac Otim, Ismail D Legason, Martin D Ogwang, Patrick Kerchan, Tobias Kinyera, Leona W Ayers, Kishor Bhatia, James J Goedert, Steven J Reynolds, Peter D Crompton, Steven C Moore, Ruin Moaddel, Demetrius Albanes, Sam M Mbulaiteye\",\"doi\":\"10.1007/s11306-024-02130-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Burkitt lymphoma (BL) is an aggressive non-Hodgkin lymphoma associated with Plasmodium falciparum and Epstein-Barr virus, both of which affect metabolic pathways. 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Unconditional, age-adjusted logistic regression analysis was used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) for the BL association with 1-standard deviation increase in the log-metabolite concentration, adjusting for multiple comparisons using false discovery rate (FDR) thresholds and Bonferroni correction.</p><p><strong>Results: </strong>Compared to controls, levels for 42 metabolite concentrations differed in BL cases (FDR < 0.001), including triacylglyceride (18:0_38:6), alpha-aminobutyric acid (AABA), ceramide (d18:1/20:0), phosphatidylcholine ae C40:6 and phosphatidylcholine C38:6 as the top signals associated with BL (ORs = 6.9 to 14.7, P < 2.4✕10<sup>- 4</sup>). 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引用次数: 0
摘要
简介伯基特淋巴瘤（Burkitt lymphoma，BL）是一种侵袭性非霍奇金淋巴瘤，与恶性疟原虫和爱泼斯坦-巴尔病毒（Epstein-Barr virus）有关，这两种病毒都会影响代谢途径。BL的代谢组学模式尚不清楚：我们使用液相色谱-串联质谱法测量了25名患有BL的男性儿童（6-11岁）和25名无癌症的地区和年龄频率匹配的男性对照者的化疗前血浆样本中的627种代谢物，这些男性对照者来自乌干达的 "东非儿童和未成年人伯基特淋巴瘤流行病学研究"（Epidemiology of Burkitt Lymphoma in East African Children and Minors study）。采用无条件、年龄调整的逻辑回归分析估算了代谢物浓度对数增加1个标准差与BL相关性的几率比（OR）及其95%置信区间（CI），并使用错误发现率（FDR）阈值和Bonferroni校正对多重比较进行了调整：与对照组相比，BL 病例中有 42 种代谢物浓度水平存在差异（FDR - 4）。采用逐步逻辑回归法选出的两种代谢物（三酰甘油（18:0_38:6）和 AABA）可将 BL 病例与对照组区分开来，曲线下面积为 0.97（95% CI：0.94，1.00）：我们的研究结果证明，血浆代谢物作为BL风险/诊断的潜在生物标志物值得进一步研究。
Plasma metabolites in childhood Burkitt lymphoma cases and cancer-free controls in Uganda.
Introduction: Burkitt lymphoma (BL) is an aggressive non-Hodgkin lymphoma associated with Plasmodium falciparum and Epstein-Barr virus, both of which affect metabolic pathways. The metabolomic patterns of BL is unknown.
Materials and methods: We measured 627 metabolites in pre-chemotherapy treatment plasma samples from 25 male children (6-11 years) with BL and 25 cancer-free area- and age-frequency-matched male controls from the Epidemiology of Burkitt Lymphoma in East African Children and Minors study in Uganda using liquid chromatography-tandem mass spectrometry. Unconditional, age-adjusted logistic regression analysis was used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) for the BL association with 1-standard deviation increase in the log-metabolite concentration, adjusting for multiple comparisons using false discovery rate (FDR) thresholds and Bonferroni correction.
Results: Compared to controls, levels for 42 metabolite concentrations differed in BL cases (FDR < 0.001), including triacylglyceride (18:0_38:6), alpha-aminobutyric acid (AABA), ceramide (d18:1/20:0), phosphatidylcholine ae C40:6 and phosphatidylcholine C38:6 as the top signals associated with BL (ORs = 6.9 to 14.7, P < 2.4✕10- 4). Two metabolites (triacylglyceride (18:0_38:6) and AABA) selected using stepwise logistic regression discriminated BL cases from controls with an area under the curve of 0.97 (95% CI: 0.94, 1.00).
Conclusion: Our findings warrant further examination of plasma metabolites as potential biomarkers for BL risk/diagnosis.
期刊介绍：
Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:
metabolomic applications within man, including pre-clinical and clinical
pharmacometabolomics for precision medicine
metabolic profiling and fingerprinting
metabolite target analysis
metabolomic applications within animals, plants and microbes
transcriptomics and proteomics in systems biology
Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.
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