期刊
GENES & DISEASES
卷 10, 期 3, 页码 786-798出版社
KEAI PUBLISHING LTD
DOI: 10.1016/j.gendis.2021.12.015
关键词
Drug discovery; Genetics; Molecular function; Parkinson's disease; Quantitative traits
Parkinson's disease (PD) is a common neurodegenerative movement disorder in the elderly. The pathogenesis of PD is not fully understood, and there are currently no medications available to halt disease progression. Identification of causative genes and those associated with susceptibility to PD is crucial for the development of new therapeutic approaches. By reviewing relevant data, this study explores the roles of different genes and molecular pathways in the pathogenesis of PD, with the aim of improving consultation and personalized medicine for PD patients in the future.
Parkinson's disease (PD) is the most common neurodegenerative movement disor-der in the elderly. As the pathogenesis of PD is still not fully understood, medications with the capacity of halting the disease progression are currently unavailable. The discovery of genes that are causative for, or increase susceptibility to PD is pivotal for the development of novel therapeutic approaches, as they are critical for the onset of PD and the molecular pathways underlying its pathogenesis. By reviewing relevant data, we discuss causative genes, and those associated with PD susceptibility and quantitative traits. Through Gene Ontology database and STRING analysis, we emphasize the roles of inorganic cation transmembrane transport pathways and hypothalamic pituitary thyroid axis, in addition to the established roles of inflammation/oxidative stress and mitochondrial dysfunction in the pathogenesis of PD. It is hoped these insights 1) untangle the clinical complex presentations of PD, 2) reveal the inter-woven molecular network leading to PD, and 3) identify critical molecular targets to facilitate novel PD drug discovery, with a view to providing improved consultation and personalized med-icine for patients with PD in the future. 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/).
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