Maastricht Multimodal Molecular Imaging Institute (M4I) , Maastricht University , Universiteitssingel 50 , 6229 ER Maastricht , The Netherlands.
Icometrix , 3012 Leuven , Belgium.
Anal Chem. 2018 Apr 17;90(8):5130-5138. doi: 10.1021/acs.analchem.7b05215. Epub 2018 Apr 3.
Hepatocellular lipid accumulation characterizes nonalcoholic fatty liver disease (NAFLD). However, the types of lipids associated with disease progression are debated, as is the impact of their localization. Traditional lipidomics analysis using liver homogenates or plasma dilutes and averages lipid concentrations, and does not provide spatial information about lipid distribution. We aimed to characterize the distribution of specific lipid species related to NAFLD severity by performing label-free molecular analysis by mass spectrometry imaging (MSI). Fresh frozen liver biopsies from obese subjects undergoing bariatric surgery ( n = 23) with various degrees of NAFLD were cryosectioned and analyzed by matrix-assisted laser desorption/ionization (MALDI)-MSI. Molecular identification was verified by tandem MS. Tissue sections were histopathologically stained, annotated according to the Kleiner classification, and coregistered with the MSI data set. Lipid pathway analysis was performed and linked to local proteome networks. Spatially resolved lipid profiles showed pronounced differences between nonsteatotic and steatotic tissues. Lipid identification and network analyses revealed phosphatidylinositols and arachidonic acid metabolism in nonsteatotic regions, whereas low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) metabolism was associated with steatotic tissue. Supervised and unsupervised discriminant analysis using lipid based classifiers outperformed simulated analysis of liver tissue homogenates in predicting steatosis severity. We conclude that lipid composition of steatotic and nonsteatotic tissue is highly distinct, implying that spatial context is important for understanding the mechanisms of lipid accumulation in NAFLD. MSI combined with principal component-linear discriminant analysis linking lipid and protein pathways represents a novel tool enabling detailed, comprehensive studies of the heterogeneity of NAFLD.
肝细胞内脂质蓄积是诊断非酒精性脂肪性肝病(NAFLD)的一个特征。然而,与疾病进展相关的脂质类型及其定位仍存在争议。传统的使用肝匀浆或血浆进行的脂质组学分析会稀释和平均化脂质浓度,并且无法提供关于脂质分布的空间信息。我们旨在通过进行无标记分子分析质谱成像(MSI)来描述与 NAFLD 严重程度相关的特定脂质种类的分布。对接受减肥手术(n = 23)的肥胖患者的新鲜冷冻肝活检进行冷冻切片,并通过基质辅助激光解吸/电离(MALDI)-MSI 进行分析。通过串联质谱进行分子鉴定。对组织切片进行组织病理学染色,根据 Kleiner 分类进行注释,并与 MSI 数据集进行配准。进行脂质途径分析,并与局部蛋白质组网络相关联。空间分辨脂质谱显示非脂肪变性和脂肪变性组织之间存在明显差异。脂质鉴定和网络分析显示非脂肪变性区域的磷脂酰肌醇和花生四烯酸代谢,而低密度脂蛋白(LDL)和极低密度脂蛋白(VLDL)代谢与脂肪变性组织相关。基于脂质分类器的有监督和无监督判别分析在预测脂肪变性严重程度方面优于模拟肝组织匀浆分析。我们得出结论,脂肪变性和非脂肪变性组织的脂质组成高度不同,这意味着空间背景对于理解 NAFLD 中脂质蓄积的机制非常重要。MSI 结合主成分-线性判别分析,将脂质和蛋白质途径联系起来,代表了一种新的工具,可用于详细、全面地研究 NAFLD 的异质性。