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Discovery of Lipidome Alterations Following Traumatic Brain Injury via High-Resolution Metabolomics.
Journal of Proteome Research ( IF 3.8 ) Pub Date : 2018-04-27 , DOI: 10.1021/acs.jproteome.8b00068
Scott R Hogan 1 , John H Phan 2 , Melissa Alvarado-Velez 2 , May Dongmei Wang 2 , Ravi V Bellamkonda 2 , Facundo M Fernández 1 , Michelle C LaPlaca 2
Affiliation  

Traumatic brain injury (TBI) can occur across wide segments of the population, presenting in a heterogeneous manner that makes diagnosis inconsistent and management challenging. Biomarkers offer the potential to objectively identify injury status, severity, and phenotype by measuring the relative concentrations of endogenous molecules in readily accessible biofluids. Through a data-driven, discovery approach, novel biomarker candidates for TBI were identified in the serum lipidome of adult male Sprague–Dawley rats in the first week following moderate controlled cortical impact (CCI). Serum samples were analyzed in positive and negative modes by ultraperformance liquid chromatography–mass spectrometry (UPLC–MS). A predictive panel for the classification of injured and uninjured sera samples, consisting of 26 dysregulated species belonging to a variety of lipid classes, was developed with a cross-validated accuracy of 85.3% using omniClassifier software to optimize feature selection. Polyunsaturated fatty acids (PUFAs) and PUFA-containing diacylglycerols were found to be upregulated in sera from injured rats, while changes in sphingolipids and other membrane phospholipids were also observed, many of which map to known secondary injury pathways. Overall, the identified biomarker panel offers viable molecular candidates representing lipids that may readily cross the blood–brain barrier (BBB) and aid in the understanding of TBI pathophysiology.

中文翻译:

通过高分辨率代谢组学发现颅脑外伤后血脂组的变化。

创伤性脑损伤(TBI)可能会在整个人群中发生,呈现出的异质性使得诊断变得不一致,管理也面临挑战。生物标记物提供了通过测量容易获得的生物流体中内源性分子的相对浓度来客观地鉴定损伤状态,严重程度和表型的潜力。通过数据驱动的发现方法,在中度受控皮层撞击(CCI)后的第一周,在成年雄性Sprague-Dawley大鼠的血清脂质组中鉴定了TBI的新型生物标志物候选物。通过超高效液相色谱-质谱法(UPLC-MS)以阳性和阴性模式分析血清样品。一个预测面板,用于对受伤和未受伤的血清样本进行分类,通过使用omniClassifier软件优化特征选择,开发出包含26个失调的物种,这些物种属于各种脂质类别,其交叉验证的准确性为85.3%。发现受伤大鼠的血清中多不饱和脂肪酸(PUFA)和含PUFA的二酰基甘油被上调,同时还观察到鞘脂和其他膜磷脂的变化,其中许多映射到已知的继发性损伤途径。总体而言,已确定的生物标志物组提供了代表脂质的可行分子候选物,这些脂质很容易越过血脑屏障(BBB)并有助于了解TBI病理生理学。发现受伤大鼠的血清中多不饱和脂肪酸(PUFA)和含PUFA的二酰基甘油被上调,同时还观察到鞘脂和其他膜磷脂的变化,其中许多映射到已知的继发性损伤途径。总体而言,已确定的生物标志物组提供了代表脂质的可行分子候选物,这些脂质很容易越过血脑屏障(BBB)并有助于了解TBI病理生理学。发现受伤大鼠的血清中多不饱和脂肪酸(PUFA)和含PUFA的二酰基甘油被上调,同时还观察到鞘脂和其他膜磷脂的变化,其中许多映射到已知的继发性损伤途径。总体而言,已确定的生物标志物组提供了代表脂质的可行分子候选物,这些脂质很容易越过血脑屏障(BBB)并有助于了解TBI病理生理学。
更新日期:2018-04-28
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