Univ. Lille, Inserm, CHU-Lille, Lille Neuroscience & Cognition, F-59000 Lille, France.
Univ. Lille, Inserm, CHU-Lille, Lille Neuroscience & Cognition, F-59000 Lille, France; Département de Pharmacologie de la Faculté de Pharmacie, Univ. Lille, Lille, France.
Int Immunopharmacol. 2021 Jun;95:107526. doi: 10.1016/j.intimp.2021.107526. Epub 2021 Mar 20.
Parkinson's disease is a progressive neurodegenerative disease associated with a loss of dopaminergic neurons in the substantia nigra of the brain. Neuroinflammation, another hallmark of the disease, is thought to play an important role in the neurodegenerative process. While mitigating neuroinflammation could prove beneficial for Parkinson's disease, identifying the most relevant biological processes and pharmacological targets as well as drugs to modulate them remains highly challenging. The present study aimed to better understand the protein network behind neuroinflammation in Parkinson's disease and to prioritize possible targets for its pharmacological modulation. We first used text-mining to systematically collect the proteins significantly associated to Parkinson's disease neuroinflammation over the scientific literature. The functional interaction network formed by these proteins was then analyzed by integrating functional enrichment, network topology analysis and drug-protein interaction analysis. We identified 57 proteins significantly associated to neuroinflammation in Parkinson's disease. Toll-like Receptor Cascades as well as Interleukin 4, Interleukin 10 and Interleukin 13 signaling appeared as the most significantly enriched biological processes. Protein network analysis using STRING and CentiScaPe identified 8 proteins with the highest ability to control these biological processes underlying neuroinflammation, namely caspase 1, heme oxygenase 1, interleukin 1beta, interleukin 4, interleukin 6, interleukin 10, tumor necrosis factor alpha and toll-like receptor 4. These key proteins were indexed to be targetable by a total of 38 drugs including 27 small compounds 11 protein-based therapies. In conclusion, our study highlights key proteins in Parkinson's disease neuroinflammation as well as pharmacological compounds acting on them. As such, it may facilitate the prioritization of biomarkers for the development of diagnostic, target-engagement assessment and therapeutic tools against Parkinson's disease.
帕金森病是一种进行性神经退行性疾病，与大脑黑质中的多巴胺能神经元丧失有关。神经炎症是该疾病的另一个标志，被认为在神经退行性过程中发挥重要作用。虽然减轻神经炎症可能对帕金森病有益，但确定最相关的生物学过程和药理学靶点以及调节它们的药物仍然极具挑战性。本研究旨在更好地了解帕金森病神经炎症背后的蛋白质网络，并确定其药理学调节的可能靶点。我们首先使用文本挖掘系统地收集与帕金森病神经炎症相关的蛋白质。然后，通过整合功能富集、网络拓扑分析和药物-蛋白质相互作用分析，分析这些蛋白质形成的功能互作网络。我们确定了 57 种与帕金森病神经炎症显著相关的蛋白质。Toll 样受体级联以及白细胞介素 4、白细胞介素 10 和白细胞介素 13 信号转导似乎是最显著富集的生物学过程。使用 STRING 和 CentiScaPe 的蛋白质网络分析确定了 8 种具有最高能力控制这些神经炎症潜在生物学过程的蛋白质，即半胱氨酸天冬氨酸蛋白酶 1、血红素加氧酶 1、白细胞介素 1β、白细胞介素 4、白细胞介素 6、白细胞介素 10、肿瘤坏死因子α和 Toll 样受体 4。这些关键蛋白质被索引为可被总共 38 种药物靶向，包括 27 种小分子和 11 种蛋白质疗法。总之，我们的研究强调了帕金森病神经炎症中的关键蛋白质以及作用于它们的药理学化合物。因此，它可能有助于优先选择生物标志物，用于开发针对帕金森病的诊断、靶标结合评估和治疗工具。
