Cozzolino Rosaria, De Magistris Laura, Saggese Paola, Stocchero Matteo, Martignetti Antonella, Di Stasio Michele, Malorni Antonio, Marotta Rosa, Boscaino Floriana, Malorni Livia
Institute of Food Science, National Council of Research, via Roma 64, 83100, Avellino, Italy,
Anal Bioanal Chem. 2014 Jul;406(19):4649-62. doi: 10.1007/s00216-014-7855-z. Epub 2014 May 15.
Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders which have a severe life-long effect on behavior and social functioning, and which are associated with metabolic abnormalities. Their diagnosis is on the basis of behavioral and developmental signs usually detected before three years of age, and there is no reliable biological marker. The objective of this study was to establish the volatile urinary metabolomic profiles of 24 autistic children and 21 healthy children (control group) to investigate volatile organic compounds (VOCs) as potential biomarkers for ASDs. Solid-phase microextraction (SPME) using DVB/CAR/PDMS sorbent coupled with gas chromatography-mass spectrometry was used to obtain the metabolomic information patterns. Urine samples were analyzed under both acid and alkaline pH, to profile a range of urinary components with different physicochemical properties. Multivariate statistics techniques were applied to bioanalytical data to visualize clusters of cases and to detect the VOCs able to differentiate autistic patients from healthy children. In particular, orthogonal projections to latent structures discriminant analysis (OPLS-DA) achieved very good separation between autistic and control groups under both acidic and alkaline pH, identifying discriminating metabolites. Among these, 3-methyl-cyclopentanone, 3-methyl-butanal, 2-methyl-butanal, and hexane under acid conditions, and 2-methyl-pyrazine, 2,3-dimethyl-pyrazine, and isoxazolo under alkaline pH had statistically higher levels in urine samples from autistic children than from the control group. Further investigation with a higher number of patients should be performed to outline the metabolic origins of these variables, define a possible association with ASDs, and verify the usefulness of these variables for early-stage diagnosis.
自闭症谱系障碍(ASD)是一组神经发育障碍,对行为和社交功能有严重的终身影响,且与代谢异常有关。其诊断基于通常在三岁前检测到的行为和发育迹象,目前尚无可靠的生物学标志物。本研究的目的是建立24名自闭症儿童和21名健康儿童(对照组)的尿液挥发性代谢组学图谱,以研究挥发性有机化合物(VOC)作为ASD潜在生物标志物的可能性。采用DVB/CAR/PDMS吸附剂的固相微萃取(SPME)结合气相色谱-质谱联用技术来获取代谢组学信息模式。在酸性和碱性pH条件下对尿液样本进行分析,以描绘一系列具有不同理化性质的尿液成分。将多元统计技术应用于生物分析数据,以可视化病例聚类并检测能够区分自闭症患者和健康儿童的VOC。特别是,正交投影到潜在结构判别分析(OPLS-DA)在酸性和碱性pH条件下均实现了自闭症组和对照组之间的良好分离,识别出了具有鉴别作用的代谢物。其中,酸性条件下的3-甲基环戊酮、3-甲基丁醛、2-甲基丁醛和己烷,以及碱性pH条件下的2-甲基吡嗪、2,3-二甲基吡嗪和异恶唑在自闭症儿童尿液样本中的含量在统计学上高于对照组。应进行更多患者的进一步研究,以勾勒出这些变量的代谢起源,确定与ASD的可能关联,并验证这些变量对早期诊断的有用性。