Institute of Biomedicine, University of Eastern Finland, Kuopio 70210, Finland.
Proteome Sciences plc, Cobham, London WC1H 9BB, United Kingdom.
Neurobiol Dis. 2019 Apr;124:454-468. doi: 10.1016/j.nbd.2018.12.009. Epub 2018 Dec 15.
No single-omic approach completely elucidates the multitude of alterations taking place in Alzheimer's disease (AD). Here, we coupled transcriptomic and phosphoproteomic approaches to determine the temporal sequence of changes in mRNA, protein, and phosphopeptide expression levels from human temporal cortical samples, with varying degree of AD-related pathology. This approach highlighted fluctuation in synaptic and mitochondrial function as the earliest pathological events in brain samples with AD-related pathology. Subsequently, increased expression of inflammation and extracellular matrix-associated gene products was observed. Interaction network assembly for the associated gene products, emphasized the complex interplay between these processes and the role of addressing post-translational modifications in the identification of key regulators. Additionally, we evaluate the use of decision trees and random forests in identifying potential biomarkers differentiating individuals with different degree of AD-related pathology. This multiomic and temporal sequence-based approach provides a better understanding of the sequence of events leading to AD.
没有单一的组学方法可以完全阐明阿尔茨海默病（AD）中发生的多种改变。在这里，我们结合转录组学和磷酸化蛋白质组学方法，从具有不同程度 AD 相关病理学的人类颞叶皮质样本中确定 mRNA、蛋白质和磷酸肽表达水平的时间顺序变化。这种方法突出了突触和线粒体功能的波动是具有 AD 相关病理学的脑样本中最早的病理事件。随后，观察到炎症和细胞外基质相关基因产物的表达增加。相关基因产物的相互作用网络组装强调了这些过程之间的复杂相互作用以及在确定关键调节剂时解决翻译后修饰的作用。此外，我们评估了决策树和随机森林在识别区分具有不同程度 AD 相关病理学的个体的潜在生物标志物中的用途。这种基于多组学和时间序列的方法提供了对导致 AD 的事件序列的更好理解。
