Joseloff Elizabeth, Sha Wei, Bell Sara C, Wetmore Diana R, Lawton Kay A, Milburn Michael V, Ryals John A, Guo Lining, Muhlebach Marianne S
Cystic Fibrosis Foundation Therapeutics (CFFT), Inc., Bethesda, Maryland.
Pediatr Pulmonol. 2014 May;49(5):463-72. doi: 10.1002/ppul.22859. Epub 2013 Jul 12.
Cystic fibrosis (CF) is a multi-system disease affecting multiple organs and cells besides the respiratory system. Metabolomic profiling allows simultaneous detection of biochemicals originating from cells, organs, or exogenous origin that may be valuable for monitoring of disease severity or in diagnosis.
We hypothesized that metabolomics using serum from children would differentiate CF from non-CF lung disease subjects and would provide insight into metabolism in CF.
Serum collected from children with CF (n = 31) and 31 age and gender matched children with other lung diseases was used for metabolomic profiling by gas- and liquid-chromatography. Relative concentration of metabolites was compared between the groups using partial least square discriminant analyses (PLS-DA) and linear modeling.
A clear separation of the two groups was seen in PLS-DA. Linear model found that among the 459 detected metabolites 92 differed between CF and non-CF. These included known biochemicals in lipid metabolism, oxidants, and markers consistent with abnormalities in bile acid processing. Bacterial metabolites were identified and differed between the groups indicating intestinal dysbiosis in CF. As a novel finding several pathways were markedly different in CF, which jointly point towards decreased activity in the β-oxidation of fatty acids. These pathways include low ketone bodies, low medium chain carnitines, elevated di-carboxylic acids and decreased 2-hydroxybutyrate from amino acid metabolism in CF compared to non-CF.
Serum metabolomics discriminated CF from non-CF and show altered cellular energy metabolism in CF potentially reflecting mitochondrial dysfunction. Future studies are indicated to examine their relation to the underlying CF defect and their use as biomarkers for disease severity or for cystic fibrosis transmembrane regulator (CFTR) function in an era of CFTR modifying drugs.
囊性纤维化(CF)是一种多系统疾病,除呼吸系统外还影响多个器官和细胞。代谢组学分析能够同时检测源自细胞、器官或外源性的生物化学物质,这对于监测疾病严重程度或诊断可能具有重要价值。
我们假设,利用儿童血清进行代谢组学分析能够区分CF患者与非CF肺部疾病患者,并有助于深入了解CF的代谢情况。
收集31例CF患儿以及31例年龄和性别匹配的患有其他肺部疾病的儿童的血清,采用气相色谱和液相色谱进行代谢组学分析。使用偏最小二乘判别分析(PLS-DA)和线性模型比较两组之间代谢物的相对浓度。
PLS-DA显示两组之间有明显区分。线性模型发现,在检测到的459种代谢物中,有92种在CF组和非CF组之间存在差异。这些代谢物包括脂质代谢、氧化剂方面的已知生物化学物质,以及与胆汁酸加工异常一致的标志物。鉴定出了细菌代谢物,且两组之间存在差异,表明CF患者存在肠道菌群失调。作为一项新发现,CF中有几条代谢途径明显不同,共同指向脂肪酸β氧化活性降低。与非CF组相比,CF组的这些途径包括酮体水平低、中链肉碱水平低、二羧酸水平升高以及氨基酸代谢产生的2-羟基丁酸水平降低。
血清代谢组学能够区分CF与非CF疾病,并显示CF患者细胞能量代谢发生改变,这可能反映了线粒体功能障碍。未来的研究旨在探讨它们与CF潜在缺陷的关系,以及在CFTR修饰药物时代,它们作为疾病严重程度或囊性纤维化跨膜传导调节因子(CFTR)功能生物标志物的用途。