Krokidis Marios G
Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Greece.
AIMS Neurosci. 2019 Dec 26;6(4):333-345. doi: 10.3934/Neuroscience.2019.4.333. eCollection 2019.
Parkinson's disease (PD) is associated with a selective loss of the neurons in the midbrain area called the substantia nigra pars compacta and the loss of projecting nerve fibers in the striatum. Predominant pathological hallmarks of PD are the degeneration of discrete neuronal populations and progressive accumulation of α-synuclein-containing intracytoplasmic inclusions called Lewy bodies and dystrophic Lewy neuritis. There is currently no therapy to terminate or delay the neurodegenerative process as the exact mechanisms underlying the pathogenesis of PD require further investigation. The identification and validation of novel biomarkers for the diagnosis of PD is a great challenge using contemporary approaches and optimizing sampling handling as well as interpretation using bioinformatics analysis. In this review, recent evidences associated with multi-omic data-sets and molecular mechanisms underlying PD are examined. A combined mapping of several transcriptional evidences could establish a patient-specific signature for early diagnose of PD though eligible systems biology tools, which can also help develop effective drug-based therapeutic approaches.
帕金森病(PD)与中脑区域黑质致密部的神经元选择性丧失以及纹状体中投射神经纤维的丧失有关。PD的主要病理特征是离散神经元群体的退化以及称为路易小体和营养不良性路易神经炎的含α-突触核蛋白的胞质内包涵体的逐渐积累。由于PD发病机制的确切机制需要进一步研究,目前尚无终止或延缓神经退行性过程的疗法。使用当代方法并优化采样处理以及利用生物信息学分析进行解释,来识别和验证用于PD诊断的新型生物标志物是一项巨大挑战。在本综述中,研究了与多组学数据集和PD潜在分子机制相关的最新证据。通过合适的系统生物学工具,对多个转录证据进行联合映射可以建立用于PD早期诊断的患者特异性特征,这也有助于开发有效的基于药物的治疗方法。