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【目的】对孤独症和正常儿童进行血清代谢组学分析,找出特异性代谢产物,为孤独症的早期筛查诊断提供实验依据。【方法】采用超高效液相色谱与四级杆飞行时间串联质谱仪联用技术(UPLC/Q-TOF MSMS)和模式识别方法,对孤独症儿童(n=73)和正常对照儿童(n=63)的血清进行代谢组学分析,找出与孤独症相关的特异性代谢产物。【结果】主成分分析得分图显示孤独症组和对照组形成明显的分类,说明孤独症血清代谢谱发生了明显改变,在正离子模式和负离子模式下共鉴定出14个潜在生物标志物。孤独症组的鞘脂类和溶血磷脂类物质明显增多,而多元不饱和脂肪酸(PUFAs)和脂酰肉毒碱明显减少。【结论】孤独症患儿和正常对照组在血清代谢水平上存在明显差异。此发现为找出孤独症诊断的潜在标志物提供了新的依据,并为孤独症的干预提供新的靶点。
【Objective】 Serum metabolomics analysis of autism and normal children was carried out to find out the specific metabolites and provide experimental evidence for the early screening diagnosis of autism. 【Methods】 Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC / Q-TOF MSMS) and pattern recognition were used to detect autistic children (n = 73) and normal control children 63) were analyzed by metabonomics to identify specific metabolites associated with autism. [Results] The score of principal component analysis showed that the autism group and the control group formed a clear classification, indicating that the serum metabolic profile of autism changed significantly. A total of 14 potential biomarkers were identified in positive mode and negative mode. In the autism group, sphingolipids and lysophospholipids increased significantly, while polyunsaturated fatty acids (PUFAs) and acylcarnitine significantly decreased. 【Conclusion】 There is a significant difference in the serum metabolic level between children with autism and normal control group. This finding provides a new basis for identifying potential markers of autism diagnosis and provides a novel target for autism intervention.