Avisar Hila, Guardia-Laguarta Cristina, Surface Matthew, Papagiannakis Nikos, Maniati Matina, Antonellou Roubina, Papadimitriou Dimitra, Koros Christos, Athanassiadou Aglaia, Przedborski Serge, Lerner Boaz, Stefanis Leonidas, Area-Gomez Estela, Alcalay Roy N
Department of Industrial Engineering & Management, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA.
NPJ Parkinsons Dis. 2022 Apr 25;8(1):52. doi: 10.1038/s41531-022-00313-y.
Lipid profiles in biological fluids from patients with Parkinson's disease (PD) are increasingly investigated in search of biomarkers. However, the lipid profiles in genetic PD remain to be determined, a gap of knowledge of particular interest in PD associated with mutant α-synuclein (SNCA), given the known relationship between this protein and lipids. The objective of this research is to identify serum lipid composition from SNCA A53T mutation carriers and to compare these alterations to those found in cells and transgenic mice carrying the same genetic mutation. We conducted an unbiased lipidomic analysis of 530 lipid species from 34 lipid classes in serum of 30 participants with SNCA mutation with and without PD and 30 healthy controls. The primary analysis was done between 22 PD patients with SNCA+ (SNCA+/PD+) and 30 controls using machine-learning algorithms and traditional statistics. We also analyzed the lipid composition of human clonal-cell lines and tissue from transgenic mice overexpressing the same SNCA mutation. We identified specific lipid classes that best discriminate between SNCA+/PD+ patients and healthy controls and found certain lipid species, mainly from the glycerophosphatidylcholine and triradylglycerol classes, that are most contributory to this discrimination. Most of these alterations were also present in human derived cells and transgenic mice carrying the same mutation. Our combination of lipidomic and machine learning analyses revealed alterations in glycerophosphatidylcholine and triradylglycerol in sera from PD patients as well as cells and tissues expressing mutant α-Syn. Further investigations are needed to establish the pathogenic significance of these α-Syn-associated lipid changes.
为寻找生物标志物，人们越来越多地对帕金森病（PD）患者生物体液中的脂质谱进行研究。然而，遗传性帕金森病的脂质谱仍有待确定，鉴于突变的α-突触核蛋白（SNCA）与脂质之间的已知关系，这一知识空白在与突变α-突触核蛋白相关的帕金森病中尤为引人关注。本研究的目的是确定SNCA A53T突变携带者的血清脂质组成，并将这些变化与携带相同基因突变的细胞和转基因小鼠中的变化进行比较。我们对30名有或无帕金森病的SNCA突变参与者以及30名健康对照者的血清中34种脂质类别中的530种脂质进行了无偏脂质组学分析。主要分析是在22名SNCA+（SNCA+/PD+）帕金森病患者和30名对照者之间使用机器学习算法和传统统计方法进行的。我们还分析了过表达相同SNCA突变的人类克隆细胞系和转基因小鼠组织的脂质组成。我们确定了最能区分SNCA+/PD+患者和健康对照者的特定脂质类别，并发现了某些脂质，主要来自甘油磷脂酰胆碱和三酰甘油类别，它们对这种区分贡献最大。这些变化中的大多数也存在于携带相同突变的人类衍生细胞和转基因小鼠中。我们将脂质组学和机器学习分析相结合，揭示了帕金森病患者血清以及表达突变α-突触核蛋白的细胞和组织中甘油磷脂酰胆碱和三酰甘油的变化。需要进一步研究来确定这些与α-突触核蛋白相关的脂质变化的致病意义。
